Anthropic

Assess acquired companies’ IT environments, plan and execute secure integrations, coordinate across internal and acquired-company teams, and build repeatable automation and playbooks. | Requires 8+ years of hands-on corporate IT engineering, enterprise identity and collaboration administration, SaaS API coding, endpoint and security knowledge, and experience leading cross-team projects. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About The Role Anthropic's Corporate Systems team runs the core collaboration platforms everyone here works in and builds the tooling and automation behind IT. That responsibility extends to the companies we acquire. Their people, devices, and systems have to come into Anthropic securely. You'll own the IT side of Anthropic's acquisitions: due diligence, integration planning, and integration. Before close, you'll assess a company's IT environment and give the deal team a clear read on risk and effort. You'll define the technical integration plan and its requirements: what moves, where it lands, in what order, what has to be ready on day one, and how each security gap gets closed. After close, you'll carry out that plan and bring the company's people, devices, and systems onto our stack. This is a hands-on engineering role. You'll hold admin, write code, build automation, run the cutovers yourself and bring in other teams when the work calls for their expertise or support. You'll lead this work for IT Engineering and partner with Security, Corporate Development, Legal, People, and Finance at every stage. M&A will be your primary focus and responsibility, but you'll be a full member of the Corporate Systems team; taking part in planning and reviews, using and contributing to the team’s tooling, and contributing to the roadmap. Early on, M&A will be most of your work, including using Claude to automate the repeatable parts of diligence and integration. As that automation matures, and when M&A load is light, you'll contribute to other parts of the team’s roadmap. Responsibilities • Lead technical IT due diligence: assess a company's identity, applications, endpoints, and infrastructure, and brief the deal team on risk and effort before close • Find the gaps between an acquired environment and Anthropic's security model, rate them, and build the mitigations into the integration plan • Define the technical integration plan and its requirements: what moves, where it lands, in what order, and what has to be ready on day one • Run the integration: take over administration, migrate people, devices, and data, and retire what's no longer needed, with support from other IT Engineering teams as required. • Work with Business Technology, Client Platform, Corporate Network, IT Operations, and Security on their parts of each integration • Keep Corporate Development, Legal, People, Finance, and the acquired company's team clear on where IT stands • Build a repeatable IT M&A playbook and automate as much of it as possible with Claude • When M&A work is light, contribute to core Corporate Systems projects You may be a good fit if you have • 8+ years as a hands-on engineer in corporate IT. You have designed and shipped systems, carried out migrations or integrations yourself, and owned at least one area end-to-end, with experience supporting other areas: identity, applications, endpoints, or corporate infrastructure • Experience administering enterprise identity and collaboration platforms such as Google Workspace, Slack, and an SSO provider, and working code in Python or similar against their SaaS APIs • Working knowledge of endpoint management and security concepts, enough to lead diligence on an unfamiliar fleet • A proven ability to understand an unfamiliar IT environment quickly and deliver a prioritized view of risk to non-specialists • A record of leading technical projects that span several teams and run to a fixed date, while doing much of the engineering yourself • Comfort working autonomously, with ambiguity and confidential information • Clear communication with executives, legal and corporate development teams, and engineers at acquired companies Strong candidates may also have • Prior M&A, carve-out, or company-to-company migration experience • Experience across the full stack: endpoints, systems, applications, and infrastructure • Hands-on experience managing a device fleet or running an MDM • Experience working in or alongside a security team • A record of building tooling that replaces manual IT work • Using Claude or similar tools as a core part of how you work Representative projects • Assess an acquired company's IT environment that nobody here has seen and produce a prioritized integration plan within days • Design a way to size integration effort and risk for a company of any shape or size • Automate bringing acquired people and devices onto Anthropic's identity and device management • Write the IT risk memo for a live deal and present it to Corporate Development and Security leadership Deadline to apply: None. Applications will be received on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary $325,000—$360,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How We're Different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Manage strategic partnerships with large tech companies and lead complex negotiations coordinating cross-functional teams. | 10+ years in strategic or corporate development with experience managing large partnerships and senior executive negotiations. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We're seeking a business development lead to own Anthropic's BD partnership footprint with a small number of the world's largest and most consequential technology companies. These are not single-threaded accounts. Each relationship spans many businesses at once — consumer products, devices and operating systems, productivity and collaboration software, cloud and developer platforms, commerce, and enterprise distribution. Your job is to see the whole board, decide where Anthropic should lean in and where it shouldn't, and turn that judgment into signed deals. The center of gravity for this role is product and distribution partnerships: co-developing opportunities with partners, and structuring the commercial, technical, and go-to-market terms that make those partnerships durable. You'll typically be running several deal streams inside the same partner in parallel — at different stages, with different counterparts, and with terms that interact with one another — and you'll be the person responsible for keeping them coherent. This is an individual contributor role for a seasoned dealmaker who is comfortable as the primary counterpart to senior executives at very large companies, who brings strong judgment to ambiguous, high-stakes situations, and who can carry a complex, multi-party negotiation from first conversation through signature and into execution. Key responsibilities Manage a small number of large, multi-faceted partner relationships end to end: set the strategy for each relationship, decide which opportunities to pursue and in what order, and stay accountable for the overall health and commercial output of the partnership across every surface it touches Lead product partnerships: identify and structure opportunities to embed Claude in partners' consumer and enterprise products, co-develop new products and features, and define the product, technical, data, and brand terms that come with them, working closely with Anthropic's product and engineering leaders Run multiple deal streams in parallel: manage several concurrent negotiations within the same partner — product integrations, distribution and go-to-market, commercial and consumption agreements, and infrastructure — and sequence and connect them so terms in one stream reinforce rather than undercut the others Negotiate complex, first-of-kind agreements: lead end-to-end negotiations involving novel commercial structures, revenue and economics sharing, product and roadmap commitments, exclusivity and competitive provisions, data terms, and multi-year, multi-component value exchanges Act as an executive counterpart: build and manage relationships with senior executives and their teams on the partner side, serve as Anthropic's primary voice into the partnership, and prepare and steer Anthropic's own executives through partner-level engagements Exercise judgment on behalf of Anthropic: weigh commercial upside against strategic, competitive, product, and mission considerations; know when to say no; and make clear, well-reasoned recommendations to Anthropic leadership on trade-offs that don't have a playbook Drive cross-functional execution: coordinate Product, Engineering, Sales, Marketing, Finance, Legal, and Policy across the life of a partnership, from initial structuring through negotiation, launch, and ongoing governance, ensuring what we sign is something Anthropic can deliver Minimum qualifications Direct experience owning a large, multi-business partner relationship, where you were responsible for the whole relationship rather than a single deal or product line Track record of structuring and closing product partnerships — embedding technology into partner products, co-developed products, distribution through partner surfaces, or similar — in addition to conventional commercial agreements Experience personally leading complex, multi-stakeholder negotiations with senior executives, including deals with interlocking terms, competitive sensitivities, and multi-year commitments Demonstrated ability to manage several significant negotiations at the same time without losing the thread on any of them Experience coordinating cross-functional execution (e.g., Product, Engineering, Legal, Finance) to bring a complex agreement from structuring through signature and delivery Preferred qualifications 10+ years in strategic business development, strategic partnerships, or corporate development at technology companies, with meaningful time spent managing relationships with very large technology partners Experience on either side of a partnership between a foundation model or AI platform provider and a large technology company Experience working inside one of the very large technology companies, with a practical understanding of how decisions get made, who holds budget and roadmap authority, and how to navigate them Experience with partnerships that span both consumer and enterprise businesses, or that combine product, distribution, and infrastructure components in a single relationship Understanding of foundation model capabilities and how they translate into partner products, with enough technical fluency to work credibly with product and engineering leaders on both sides Background in corporate development, strategy, or a legal or finance discipline involving structuring and papering unusually complex agreements The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000—$365,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Build and operate secure cloud infrastructure and data pipelines to meet legal and technical requirements, partnering with internal teams to translate legal obligations into scalable and auditable systems. | Extensive experience designing and operating trusted production infrastructure and data systems, securing cloud environments, and communicating technical constraints to nontechnical stakeholders. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Legal Tech engineers play a specialized and critical role in keeping Claude at the frontier. Partnering closely with counsel, we provide custom infrastructure and guidance for complex, novel technical matters, empowering teams across the company to continue meeting our legal obligations as we innovate. As a Senior+ Software Engineer on our Legal Tech team, you'll build dedicated, highly secure, and reliable cloud environments and data processing and storage capabilities at speed and scale. You will own your scope end to end: from raw requirements all the way through to large-scale production systems that satisfy legal invariants and unlock new possibilities. The systems you build won't just be dependable and scalable; they'll be interpretable and auditable, demonstrating to skeptical audiences exactly how they worked and why results can be trusted. You'll be an essential member of a collaborative team, working together to solve difficult problems against fixed deadlines. You will own internal customer relationships as well: you'll gather, prioritize, and coordinate needs from colleagues on Privacy, Security, Research, and/or Infra as well as Legal, to ship the right capabilities on the right timelines. You'll act as a trusted advisor: clearly explaining technical concepts and constraints to inform legal decisions, and proactively designing new approaches to prevent classes of problems. Your infrastructure expertise will directly empower our business to calibrate and manage risk, innovating faster thanks to systems that build in legal considerations. Key responsibilities Build and operate dedicated cloud infrastructure, storage, and data pipelines for specialized workloads that can't run on general-purpose systems Design architectures with excellent security, privacy, reliability, scalability, and auditability baked in Partner with a wide range of internal customer teams to translate requirements into sound approaches and realistic ETAs Deliver against fixed deadlines Support complex and novel legal requests on controlled infrastructure, with verifiable chain of custody Pair with engineering teams across the company to extend existing infrastructure to support new workflows and/or legal requests Work with nontechnical stakeholders to clarify their needs through responsive, easy-to-follow dialogue Minimum qualifications Experience designing, building, and operating highly trusted infrastructure and data systems in production, including owning architectural decisions Experience working across large, complex, multi-team environments, including in stacks and code you don't own Ability to take ownership of a cloud account and secure it end to end (networking, storage, identity, encryption, least-privilege provisioning, etc.) on AWS and/or GCP Ability to translate legal and privacy requirements into sound technical designs and implementations that teams are excited to adopt A habit of verifying rather than assuming: designing checks for invariants and plainly naming what isn't proved Self-directed in a high-change environment, and comfortable resequencing quickly when new needs emerge Clear communication with nontechnical stakeholders, and an understanding of their needs Preferred qualifications Software engineering experience with an infrastructure, data, privacy, and/or security focus Proficiency with large-scale data tooling, such as distributed processing, lakehouse table formats, and/or query engines Understanding of data processing pipelines, LLM training, and/or provenance and lineage Experience with secure enclaves, confidential computing, clean rooms, or other purpose-built environments for sensitive data Background in eDiscovery, litigation support, or records retention at scale, including chain of custody and verifiable integrity The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Design and own backend services and infrastructure to scale cloud inference across multiple providers while optimizing resources and ensuring reliability. | Requires significant experience with high-performance distributed systems and major cloud platforms, autonomy, collaboration, and complex hardware/networking knowledge. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations. Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources: compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need product-minded backend engineers who can navigate these platform differences, design the services and abstractions that work across providers, and make architectural decisions that keep us reliable and cost-effective at massive scale. Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards. Key responsibilities Design, build, and own backend services and infrastructure that serve Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models Work cross-functionally with internal inference, product API, systems, and security teams, among others, and with CSP partners to stand up the full serving stack on new cloud platforms, resolve operational issues, and influence provider roadmaps Build and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity Contribute to capacity planning, autoscaling, and workload routing strategies that match supply with demand and direct requests to the most cost-effective accelerator and region Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads Minimum qualifications Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration Are curious about LLM serving; prior inference or ML experience is not required Thrive in cross-functional collaboration with both internal teams and external partners Have experience working with external partners to align goals and deliver impact Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description Preferred qualifications Direct experience working with CSPs to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments Solid understanding of multi-region deployments, geographic routing, and global traffic management Proficiency in Python or Rust The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Design and maintain high-performance distributed systems for AI model serving and optimize compute efficiency. | Significant software engineering experience with distributed systems, cloud infrastructure, and machine learning systems. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researchers to develop next-generation models Integrate new AI accelerator platforms and support inference for new model architectures Minimum qualifications Significant software engineering experience, particularly with distributed systems Results-oriented, with a bias towards flexibility and impact Willingness to pick up slack, even if it goes outside your job description Desire to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Preferred qualifications Experience with high-performance, large-scale distributed systems Experience implementing and deploying machine learning systems at scale Experience with load balancing, request routing, or traffic management systems Familiarity with LLM inference optimization, batching, and caching strategies Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure) Proficiency in Python or Rust Representative projects Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads Building production-grade deployment pipelines for releasing new models to millions of users reliably Contributing to new inference features Supporting inference for new model architectures Analyzing observability data to tune performance based on real-world production workloads Managing multi-region deployments and geographic routing for global customers The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Own end-to-end delivery of computer-use and browser-control product features and partner with researchers to improve reliability and user experience. | Strong full-stack engineering skills, experience shipping products from zero to one, hands-on with LLM APIs and agent frameworks, and iterative user feedback incorporation. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Computer Use team teaches Claude to see and operate computer interfaces, and builds the agent harness and end-user products that turn that capability into real tools. The team sits inside Anthropic's research organization and closes the loop between product and model. As a Product Engineer on this team, you'll own end-to-end delivery of our computer-use and browser-control product surfaces. You'll build across the full stack, from the user interface to the agent runtime to the backend services behind it. You'll work directly alongside researchers, with no layers between you and the model or the user. This is a dynamic role in which priorities evolve frequently. Success depends on a high tolerance for ambiguity, the adaptability to shift focus as needs change, and the agility and discernment to continuously prioritize the highest impact work. Key responsibilities Own end-to-end delivery of computer-use and browser-control product surfaces: scope, build, ship, measure, and iterate Diagnose and resolve reliability and robustness issues in the computer-use agent harness that block real-world usage Partner with computer-use researchers Partner with the Claude Cowork team on shared surfaces, integrations, and knowledge-worker workflows Instrument products and use usage data to drive prioritization and measure progress Translate fuzzy user pain points into concrete, shippable features for knowledge workers Minimum qualifications Experience building and shipping a product from zero to one with end-to-end ownership, as a founding or early engineer at a startup or with equivalent ownership inside a larger company Strong full-stack engineering skills, including production web frontend and backend development Hands-on experience building with LLM APIs, prompting, or agent frameworks A track record of shipping to external users and iterating based on their feedback Preferred qualifications Strong product design instincts and the ability to produce a clean, usable interface without a dedicated designer Experience with browser automation, desktop automation, or robotic process automation systems Experience building evals or quality harnesses for machine learning systems Comfort with lightweight data analysis, such as SQL, notebooks, and defining and tracking product metrics Experience designing agent loops, tool integrations, or guardrails for LLM-based systems Representative projects Own and resolve the top reliability and robustness issues on the computer-control and browser-control product surfaces, with measurable improvement in task success rate Take a net-new computer-use powered workflow from concept to external users, including instrumentation and a readout on usage The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000—$320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Build and maintain identity and access management infrastructure to secure AI capabilities. | Bachelor's degree and significant backend production experience with strong coding and collaboration skills. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As Claude's capabilities grow, so does our responsibility to ensure those capabilities reach the right people. The Access Programs team builds the systems that verify who our customers are, grant access to advanced model capabilities for approved use cases, and ensure that access is not misused. As a software engineer on this team, you will build the identity, vetting, and access management infrastructure that underpins our trusted access programs, along with the monitoring and enforcement tooling that keeps them safe. This work sits at the center of how Anthropic deploys frontier capabilities responsibly, balancing broad access with rigorous safeguards. Responsibilities: Build identity verification and vetting systems (KYC/KYB) that establish who our individual and business customers are Design and implement access control systems that grant, scope, and revoke access to advanced capabilities based on approved use cases Build infrastructure to configure safety systems and detection thresholds on a per-customer basis for trusted access programs Develop monitoring to detect misuse of expanded access, and tooling that enables enforcement teams to act on it Partner closely with policy, enforcement, threat intelligence, product, research, and go-to-market teams so that access decisions are well-informed and consistently applied Build systems that identify account compromise and takeover, apply mitigations in real time, and carry affected accounts through to full remediation Design and build the dashboards, alerting, and internal admin tooling that give the team and its partners clear visibility into the health and outcomes of our access programs Integrate with third-party identity verification and data enrichment vendors You may be a good fit if you have: A Bachelor's degree in Computer Science, Software Engineering, or comparable experience Experience building and operating backend systems in production Strong coding skills in at least one general-purpose programming language, and experience building software with AI coding tools Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders Care about the societal impacts of AI and want your work to make powerful systems safer Strong candidates may also: 8+ years of industry software engineering experience Experience building shared platforms or foundational services that many teams and products depend on, rather than one-off solutions for a single use case A track record of working across functions (for example engineering, product, policy, operations, and go-to-market) to gather requirements, reconcile competing needs, and drive adoption of what you build Experience with identity, authentication, or authorization systems at scale Experience with KYC/KYB workflows or identity verification vendors Experience in trust and safety, integrity, fraud, or abuse detection Experience detecting and responding to account takeover or credential compromise Experience partnering with operational teams to build custom internal tooling The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Rapidly prototype full-stack AI applications and collaborate with research teams to design experiments and user experiences. | 8+ years full-stack development experience with zero-to-one product work in startups, strong user-centric and hacker mentality. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications. Anthropic Labs serves as our internal accelerator. We're looking for the next breakout hits that bring substantial revenue or transform an industry. We operate in close partnership with research and build through fast iteration cycles. Past successes include Claude Code and MCP. We're seeking versatile, entrepreneurial engineers to join Labs. In this role, you'll work at the intersection of cutting-edge research and real-world application, rapidly building and testing new experiences, working directly with researchers and users, and generating the insights that shape Anthropic's product future. You'll need to be comfortable with ambiguity, willing to kill your own projects when the data says to, and energized by the pace of building in uncharted territory. Responsibilities Rapidly prototype full-stack applications that showcase emerging AI capabilities, shipping early and often to maximize learning Collaborate closely with research teams to understand new model capabilities and translate them into intuitive user experiences Work directly with internal test users and external partners to gather feedback, iterate quickly, and validate (or invalidate) product concepts Design and run structured experiments to test hypotheses, balancing creative exploration with rigorous evaluation Generate documentation and insights to guide successful prototypes toward full product teams Advocate for user experience and product considerations early in the research process Provide feedback to research teams about model effectiveness and where capabilities can be improved Flexibly contribute across Labs initiatives based on organizational priorities and emerging opportunities—context from one project should inform the next You may be a good fit if you Have 8+ years of experience building full-stack applications, with a track record of zero-to-one work in startup or startup-like environments Thrive in ambiguity and are energized (not anxious) by uncertainty—you're comfortable working on projects that might not exist in three months Have a hacker mentality: high agency, bias toward shipping, comfort with technical debt when it's the right tradeoff Are deeply user-centric—you validate ideas with actual users before over-investing and talk about problems before solutions Can articulate learnings from failed or killed projects without defensiveness; you treat your work as experiments Hold strong opinions loosely—you advocate forcefully for ideas but change your mind based on evidence Are a generalist who can transition between different problem spaces as priorities shift Work independently with good judgment about what matters, without needing constant direction Have strong technical skills across modern web development stacks (React, Node.js, Python, etc.) and are comfortable with APIs, databases, and cloud technologies Communicate effectively and translate complex AI capabilities into intuitive experiences Care about the societal impacts and ethics of your work Strong candidates may also have Experience building products that involve AI/ML components or working with large language models Experience collaborating directly with research teams in AI/ML environments Background conducting user research, interviews, and usability testing Experience across both B2B and B2C product development, or in multiple industries Design sensibility or hands-on experience with UI/UX for AI-powered applications Experience with real-time applications, WebSocket implementations, or complex frontend interactions What we're not looking for at this stage Deep specialists who can't adapt if their domain becomes irrelevant Engineers who've only succeeded in big-company structures with well-defined processes and long timelines People who are precious about their work or frame all past projects as successes Those who need clear roadmaps and get stressed by shifting priorities Candidates need not have 100% of the skills listed above Formal certifications or education credentials Direct machine learning or AI research experience Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Manage end-to-end workforce lifecycle and streamline operational workflows for human review programs. | Experience managing contractor/vendor workforces, capacity planning, process optimization, and cross-functional collaboration. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Safeguards Enforcement team detects and mitigates misuse of Claude, and much of that work depends on people: a growing human review workforce made up of full-time staff, contractors, vendors and BPO partners. As that workforce scales across a widening range of harm areas, the programs that bring people in, give them the right access, and roll them off cleanly have to keep pace. As Program Manager for Safeguards Workforce Operations, you’ll own those programs end to end. You’ll run onboarding, offboarding, device provisioning and access provisioning for every worker type we use, working hands-on with the requests themselves while you build the processes that make them repeatable. You’ll partner with Enforcement leads to turn shifting priorities into capacity plans, and carry those plans through with our vendor partners. Because this role supports every Safeguards Enforcement program, you’ll also connect the dots across Anthropic, working with IT, People Operations, Security, Contingent Workforce, Human Data Operations and other teams running scaled human review to streamline practices and keep standards consistent. This is a role for someone who likes fixing broken things at speed. The landscape moves quickly, priorities change often, and the work is an even mix of direct execution and program building. Key responsibilities Own the workforce lifecycle for contractor, vendor and BPO reviewers: onboarding, offboarding, device provisioning and access provisioning Triage and execute inbound requests for new or changing vendor, BPO and contractor capacity Turn ad hoc or broken processes into scalable ones, with clear owners, service levels and a system of record Partner with IT and Security on access governance: least-privilege provisioning, timely revocation and regular access reviews Build and maintain capacity plans with Enforcement leads, translating review demand into workforce needs and adjusting as priorities shift Work with Safeguards vendor management to hold partners accountable to capacity and onboarding commitments Align practices with Human Data Operations and other teams running scaled human review, and help them streamline their own workflows Help define the long-term workforce strategy for Safeguards Enforcement Minimum qualifications Have personally run onboarding, offboarding, access and device provisioning for contractor, vendor or BPO workforces — doing the work, not only overseeing it Have operated scaled human review programs with vendors or BPOs, such as trust & safety, content moderation or data annotation operations Have taken a broken or ad hoc process, made it scalable, and brought other teams along in adopting it Understand the fundamentals of capacity planning: how volume, handle time, quality targets, ramp and attrition turn into workforce needs Exercise sound judgment on access and permissions, and know when to bring in IT or Security Move quickly and stay effective when priorities change and information is incomplete Build alignment through direct partnership with the teams you depend on Preferred qualifications Owned a vendor or BPO relationship directly, including service levels and business reviews Built formal capacity models for review or operations workforces Supported workforces across more than one enforcement or harm area Hands-on experience with device management and identity and access tooling Worked through a period of hypergrowth where programs had to mature alongside the organization The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $245,000—$285,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Lead and grow a team of engineers building full-stack internal tools to improve productivity and security and set technical direction for scalable solutions. | 7+ years software engineering experience with 2+ years management, bachelor's degree, proficiency in modern web stacks and cloud infrastructure. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic is looking for an empathetic engineering manager to lead a team building internal tools that enable and increase productivity for our employees, especially tools for security, authorization and automation. You'll partner closely with internal users to understand needs and set direction for efficient solutions, often augmenting the tools with Claude for a greater experience and impact. On the Business Technology team, we are passionate about delighting and enabling our users through thoughtful and easy-to-use everyday solutions. At Anthropic, we're building towards an ambitious mission of ensuring AI systems are safe and beneficial to humanity. Our team plays a crucial role in this mission by enabling our teams to work efficiently and securely at scale. Responsibilities Lead and grow a team of engineers building full-stack internal tools for business-critical use cases Partner with different teams to deeply understand their workflows and identify opportunities for improved productivity through engineering Set technical direction and prioritize roadmap initiatives that drive the most impact for internal users Foster a culture of rapid iteration, user feedback, and continuous improvement within the team Champion best practices in API design, security, and user experience across the team Monitor system reliability, build for operational excellence, and own incident response processes Hire, develop, and retain top engineering talent You may be a good fit if you Have 7+ years of experience in software engineering, with 2+ years in an engineering management role Have a track record of building and shipping production full-stack software with a focus on usability Have experience leading teams building and maintaining scalable internal applications and platforms Demonstrate strong technical judgment across modern web development (React, TypeScript, Node.js, Python, Go) and cloud technologies (AWS/GCP/Azure) Are skilled at translating ambiguous user needs into clear technical direction and priorities Communicate with empathy and strive to build strong relationships with stakeholders and direct reports alike Strong candidates may also Have experience building engineering roadmaps and aligning them with broader business objectives Bring a track record of developing engineers through coaching, mentoring, and structured feedback Have experience balancing trade-offs across security, privacy, reliability, and user experience at scale Have experience with Identity and Access Management tools and security best practices Excel at cross-functional collaboration and building alignment across teams with differing priorities Have experience anticipating changing business needs and translating them into adaptive technical strategies The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000—$405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Lead and manage cybersecurity operations programs, SOC teams, and incident response across multiple sectors including OT/ICS and executive protection. | Director-level experience in security operations, SOC leadership, incident command, and expertise in OT/ICS security and digital forensics. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About The Role Anthropic's Application Security team secures the systems that build, serve, and increasingly are Claude. The attack surface is unlike most AppSec work: multi-agent orchestration, sandboxed code execution, agents holding delegated credentials, untrusted tool output crossing trust boundaries — problems with little prior art and no off-the-shelf playbook. The way the team works is also different. We use Claude as our primary tool across every part of the job: it drives our static analysis, drafts and fixes vulnerabilities as pull requests, performs first-line bug bounty triage, and assists threat modeling for design reviews. The human work is the judgment layer — system-level reasoning, deciding what matters, and building the next thing the model can't do yet. This is a builder's role on a senior team. We hire engineers who ship production systems and clear a hands-on threat-modeling bar — people who can find the vulnerability but would rather build the system that finds them all. Every engineer owns a system end-to-end, and the team's work has shaped customer-facing product security — including Claude Code's security review tooling, its security guidance plugin, sandboxing, and auto mode. Key Responsibilities • Design, build, and operate Claude-powered security systems — LLM-driven code analysis, automated vulnerability remediation, AI-assisted threat modeling — and own one or more of them end-to-end, including the cross-functional relationships that come with it • Lead secure design reviews and threat modeling for novel AI systems, identifying risks that don't map to existing frameworks • Evolve a public bug bounty program where automation handles routine triage and root-cause work, and engineers handle escalations and corner cases • Partner with Product, Infrastructure, and Research teams as an embedded security owner — consulting on launches, shaping architecture, and influencing decisions where security is the constraint • Share an operational on-run rotation with the rest of the team — bounty escalations, incident response, and launch consults on systems serving Claude in production Minimum Qualifications • Hands-on application and infrastructure security experience, including cloud and containerized environments • Production-quality coding ability in at least one of Python, Go, Rust, or TypeScript, with a track record of building durable systems rather than one-off scripts • Practical threat-modeling and vulnerability-identification skills — you've found and reasoned about real bugs in real systems, even if breaking isn't your primary mode • Demonstrated ability to operate with high autonomy and ambiguity — comfortable being handed a problem and a lot of latitude rather than a spec • Clear technical communication with both engineers and leadership Preferred Qualifications • 7+ years in application security, security engineering, or security-focused software engineering • Already use LLMs as a core part of how you work, with opinions about where they help and where they don't • Experience securing agentic, code-execution, or LLM-integrated systems specifically • Prior ownership of a bug bounty program, vulnerability disclosure program, or vulnerability-management infrastructure at scale • Background building security automation or developer-facing security tooling • Offensive security or penetration testing experience Representative projects • An increasingly autonomous vulnerability pipeline — LLM-driven code analysis finds the issue, scores it for real exploitability, and opens the fix PR, with humans as the review step rather than the author • Bug bounty operations where Claude handles first-line triage and drafting, and engineers focus on the reports that actually need judgment • AI-assisted threat modeling that generates intake questions, drafts the model, and recommends which design reviews need a human in the room • Automated dependency vulnerability remediation across Anthropic's codebase • The company-wide vulnerability dashboard and SLA enforcement layer every engineering team works against • Threat models and security architecture for agentic product surfaces — code execution sandboxing, agent identity and delegated auth, tool-use boundaries The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary $320,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How We're Different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Design and implement core search systems and improve search quality metrics and tooling. | 5+ years building complex distributed systems, proficiency in Python, Go, or Java, and solid search fundamentals. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We're building Anthropic's search platform team to create scalable, efficient search capabilities that power Claude's ability to access and retrieve information. In this role, you'll design and implement core search systems from the ground up. Responsibilities: Work with a small, senior team of engineers and researchers to build Anthropic’s search platform from scratch Establish metrics and tooling to measure and improve search quality Enhance search algorithms and indexing mechanisms to boost search accuracy and efficiency You may be a good fit if you: 5+ years building complex distributed systems in production Solid grasp of search fundamentals: indexing, retrieval, ranking Strong coding skills in Python, Go, Java, or similar languages Hands-on experience with high-volume data processing architectures The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $1—$2 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Lead integrated supply planning and forecasting for data center delivery portfolio, coordinating cross-functional teams to align supply and capacity targets with site readiness. | Experience leading supply/capacity planning or portfolio management in capital-intensive infrastructure, strong cross-functional influence, and ability to build and run supply forecasts and scenarios. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About The Role Anthropic is rapidly scaling our compute infrastructure across a portfolio of data center builds with multiple developer partnerships. The Data Center Planning team owns the integrated view of that supply: compute allocation, decision locks, forecasting, and the frameworks that underpin all of it. We’re looking for a versatile Data Center Supply Planning Lead to help build the plan for data center delivery. This role has a broad view of the portfolio: you will drive the supply model that ties our compute supply and capacity targets to the site pipeline, use it to prioritize which opportunities we pursue and how we configure them, and turn the reasoning into principles as the portfolio grows. You will also have a deep understanding of our active sites, and will build supply forecasts that our partners mobilize against and internal teams rely on. This is a highly cross-functional role that will work closely with our site selection, engineering, delivery, and demand planning teams on the framework and processes that move sites to operational readiness. Responsibilities • Build the integrated data center supply forecast and planning assumptions behind it: committed plus pipeline supply - by site, design, and accelerator type - against growth targets • Own the portfolio view of chip-to-site allocation and decision cadence: surface the trade-offs, drive the lock points, and communicate changes to the broader org • Support and evolve data center portfolio reviews that ground our teams on the current state of supply, decisions needed, and downstream impacts • Partner with technical program management, delivery, and demand planning teams so that hall readiness, install plans, and chip supply stay in sync as any of the three moves • Build and run scenarios: assess what happens to the plan if a delivery date, chip tranche, or a target changes; and develop solvers that recommend how to close gaps • Plan for the long-lead resources we should hold in inventory to create optionality and how they should be allocated strategically • Shape the process by which a new site enters delivery tracking, and the change-management process by which a date change flows to downstream teams • Support the buildout of a delivery planning system-of-record; partner with our internal tooling team on the build You may be a good fit if you • Have led supply/capacity planning or portfolio management for data centers, power, or similar capital-intensive infrastructure • Have architected supply planning processes and driven their cadence with continuous improvement • Have redesigned a delivery or deployment process at scale and can point to what it improved • Know the full data center buildout lifecycle, from acquisition, design, and sourcing through construction, commissioning, and deployment • Have built planning models/tools with the goal of automation, while leveraging AI-assisted development • Proactively surface opportunities and risk across functions and drive resolution • Have a track record of driving outcomes through influence with cross-functional partners Strong candidates may also have • Capacity planning, S&OP, or deployment planning experience at a hyperscaler or large industrial operator • Supply chain, operations research, or optimization background (e.g. allocation, scheduling, design) • Experience defining requirements for, and standing up, an internal planning system-of-record • Published detailed forecasts that outside partners plan against The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary $320,000—$405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How We're Different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Lead integrated data center supply forecasting, portfolio management, and cross-functional coordination to ensure delivery and operational readiness. | Experience leading supply/capacity planning or portfolio management for data centers or similar infrastructure with strong cross-functional influence and process improvement. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About The Role Anthropic is rapidly scaling our compute infrastructure across a portfolio of data center builds with multiple developer partnerships. The Data Center Planning team owns the integrated view of that supply: compute allocation, decision locks, forecasting, and the frameworks that underpin all of it. We’re looking for a versatile Data Center Supply Planning Lead to help build the plan for data center delivery. This role has a broad view of the portfolio: you will drive the supply model that ties our compute supply and capacity targets to the site pipeline, use it to prioritize which opportunities we pursue and how we configure them, and turn the reasoning into principles as the portfolio grows. You will also have a deep understanding of our active sites, and will build supply forecasts that our partners mobilize against and internal teams rely on. This is a highly cross-functional role that will work closely with our site selection, engineering, delivery, and demand planning teams on the framework and processes that move sites to operational readiness. Responsibilities • Build the integrated data center supply forecast and planning assumptions behind it: committed plus pipeline supply - by site, design, and accelerator type - against growth targets • Own the portfolio view of chip-to-site allocation and decision cadence: surface the trade-offs, drive the lock points, and communicate changes to the broader org • Support and evolve data center portfolio reviews that ground our teams on the current state of supply, decisions needed, and downstream impacts • Partner with technical program management, delivery, and demand planning teams so that hall readiness, install plans, and chip supply stay in sync as any of the three moves • Build and run scenarios: assess what happens to the plan if a delivery date, chip tranche, or a target changes; and develop solvers that recommend how to close gaps • Plan for the long-lead resources we should hold in inventory to create optionality and how they should be allocated strategically • Shape the process by which a new site enters delivery tracking, and the change-management process by which a date change flows to downstream teams • Support the buildout of a delivery planning system-of-record; partner with our internal tooling team on the build You may be a good fit if you • Have led supply/capacity planning or portfolio management for data centers, power, or similar capital-intensive infrastructure • Have architected supply planning processes and driven their cadence with continuous improvement • Have redesigned a delivery or deployment process at scale and can point to what it improved • Know the full data center buildout lifecycle, from acquisition, design, and sourcing through construction, commissioning, and deployment • Have built planning models/tools with the goal of automation, while leveraging AI-assisted development • Proactively surface opportunities and risk across functions and drive resolution • Have a track record of driving outcomes through influence with cross-functional partners Strong candidates may also have • Capacity planning, S&OP, or deployment planning experience at a hyperscaler or large industrial operator • Supply chain, operations research, or optimization background (e.g. allocation, scheduling, design) • Experience defining requirements for, and standing up, an internal planning system-of-record • Published detailed forecasts that outside partners plan against The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary $320,000—$405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How We're Different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Build and maintain core systems for datacenter lifecycle tracking and collaborate with energy and supply chain teams to ensure data accuracy. | 8+ years software engineering experience with full-stack skills and domain experience in physical-world industries like datacenters, construction, or logistics. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications. Frontier AI runs on datacenters, and the world is in the middle of the largest infrastructure buildout in a generation. The binding constraint on progress is increasingly everything around the chips: land, power, permits, equipment, and the design and construction of the buildings themselves. Bringing a single site online involves hundreds of people, thousands of components, and decisions that move enormous amounts of capital. Much of that work still runs on spreadsheets and handoffs. At Anthropic, we're building software and Claude-powered tools to help Anthropic scale out its compute, and we think there's an enormous opportunity to rethink how that work gets done. It's early, it's already having a real impact, and the engineers who join now will shape how one of the most consequential buildouts in the world gets done. We're looking for strong, versatile software engineers who love building for people doing real work in the physical world. You'll embed with the teams that source sites, design buildings, procure equipment, and manage construction, learn their work deeply, and build the tools and systems they rely on every day. Datacenter experience is a big plus, but what matters most is that you can earn the trust of expert operators, model a messy domain cleanly, and move fast. Responsibilities Build the core systems that track a datacenter's lifecycle (sites, designs, bills of materials, equipment, and construction progress) in one trusted, permissioned source of truth Embed with datacenter, energy, and supply chain teams to understand how the work actually gets done, find the critical path, and build the tools they reach for first Bring order to messy data by migrating and reconciling spreadsheets and legacy trackers, and integrate with the industry's tools, like construction management, scheduling, and engineering systems Design for trust: fine-grained permissions, auditability, and data quality for information that steers major investment decisions Ship early, iterate with users, and cut anything that doesn't help bring compute online sooner Partner with research to understand new model capabilities and share where they fall short in engineering-heavy, physical-world domains You may be a good fit if you Have 8+ years of experience building software, with strong full-stack skills and solid grounding in data modeling, APIs, and databases Have built software that teams in a physical-world industry depend on, such as datacenters, construction, energy, manufacturing, supply chain, or logistics Have a track record of zero-to-one work in startup or startup-like environments Are deeply user-centric: you learn the domain from the people doing the work and validate with them before over-investing Bring high agency and good judgment about what matters, and hold strong opinions loosely Communicate clearly across engineering, operations, and research, and care about the societal impacts of your work Strong candidates may also have Experience in datacenters (at a hyperscaler, colocation provider, operator, utility, or engineering firm), or in adjacent fields like construction, logistics, or legal Experience with the domain's tooling, such as construction management (Procore, Autodesk Construction Cloud), scheduling (Primavera P6), PLM/BOM, ERP and procurement, CAD/BIM, DCIM, or power system studies A background in electrical, mechanical, or civil engineering, energy systems, or supply chain alongside a software career Experience building products with large language models Candidates need not have 100% of the skills listed above Formal certifications or education credentials Direct machine learning or AI research experience Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Design and operate backend systems ensuring reliability and low latency for ML token generation. | 8+ years experience in software engineering with distributed systems and production operations; LLM inference experience a plus. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: The Safeguards ML Sampling Path team builds and operates the production services that power Claude's safety systems. These services sit on the token generation path across every platform Claude runs on: every request must pass through them, and each millisecond of added latency is wait time for our users. You’ll keep p99 latency flat as traffic grows, build for robustness as dependencies time out or partially fail, and ship changes safely to a system that cannot go down. What you'll do: Design, build, and operate the backend systems that process every token on the generation path for Claude requests, including the streaming contract with the API and inference engines. Own latency and reliability end to end: define and maintain SLOs and error budgets for added latency, time-to-first-token, and availability, and lead incident response and postmortem follow-through. Ship changes to the hot path rapidly but safely — canaried and gradual rollouts, error budget and latency gating, fast rollbacks — and drive per-token performance: chase tail latency and keep cost flat as traffic, models, and checks per request grow. Set technical direction for the sampling path: lead design reviews, make latency, reliability, and cost trade-off calls with the inference and research teams, mentor engineers, and raise the operational bar for the wider Safeguards organization. You may be a good fit if you: Have designed, built, and operated high QPS systems at global scale, and were accountable for them in production: incident response, outages, and postmortem-driven remediation. Have a strong foundation in distributed systems: replication, consistency tradeoffs, failure modes, and SLO management under load. Design systems for graceful degradation: you plan for a slow dependency, a dropped stream, or a half-rolled-out deploy before it happens, and build so the system degrades predictably instead of failing. Have successfully shipped broad or all-encompassing changes to mission critical systems (e.g., database migrations, interface changes, rewrites). Strong candidates may also have: 8+ years of industry software engineering experience. Familiarity with LLM inference systems and transformer-based models (not required, but a plus). The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Design, build, and scale infrastructure supporting research workflows and lead complex engineering projects with cross-team alignment. | Experience designing and operating large-scale distributed systems or infrastructure with strong software engineering fundamentals and cross-team leadership. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Research Productivity organization builds the infrastructure and systems that accelerate research across Anthropic, including the tools that help our research process get faster and more effective over time. We're looking for an experienced software engineer to join us as we scale this infrastructure at a moment when both demand and scope are growing extremely quickly. This team operates like a startup within a startup. You'll be a strong fit if you like thinking from first principles, iterating fast on infrastructure, and tackling reliability and scalability challenges head-on as the products built on top of your systems evolve underneath you. You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make the architectural decisions that shape how the infrastructure behind our research tooling gets built. You'll partner directly with research teams to understand their workflows, anticipate how their requirements will change, and design and scale infrastructure that can keep pace. Responsibilities Design, build, and scale infrastructure and systems that support rapidly increasing usage, where requirements and workload continue to evolve as the products built on top of them evolve Independently scope and lead complex, multi-month engineering projects, from an ambiguous starting point through to a production system Drive cross-organizational alignment on technical direction, working through ambiguous problem spaces with multiple stakeholders and teams Make architectural decisions that shape the foundation of research infrastructure and tooling across Anthropic Partner directly with researchers to deeply understand their workflows, then anticipate and design for how those needs will change Iterate quickly, favoring pragmatic, first-principles solutions and fast feedback loops over heavy upfront design Take ownership of the reliability and scalability of critical systems as load, usage, and complexity increase Help set technical standards and best practices for the team, and mentor other engineers Minimum Qualifications Experience designing, building, and operating large-scale distributed systems or infrastructure in production A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects Strong software engineering fundamentals and hands-on coding ability Experience making architectural decisions that other engineers and teams build on top of Strong written and verbal communication skills, with experience driving alignment across multiple teams or stakeholders Demonstrated ability to operate effectively in ambiguous, fast-changing environments Strong candidates may also have Experience building infrastructure or platforms specifically for research or machine learning workflows Direct experience navigating the reliability and architectural challenges that come with rapidly scaling systems Experience with distributed systems, cloud infrastructure, and infrastructure-as-code Familiarity with the compute, tooling, and workflow needs of large-scale machine learning research Experience operating in a startup or startup-like environment, i.e. a small, fast-moving team with high autonomy Prior experience as a technical lead or mentor for other engineers The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000—$625,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Manage and design capabilities and processes to scale physical supply chain operations with strategic partnerships and compliance. | Experience managing warehouse or logistics operations, designing inventory systems, strong communication, and process-building skills required. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Infrastructure organization builds and operates the compute that trains and serves our frontier models. Behind every cluster is a physical supply chain: servers, accelerators, networking equipment, spares, and tooling that have to be received, inspected, secured, tracked, and delivered to the right site at the right time. The Warehousing and Logistics team owns that flow, and this role builds the key capabilities and partnerships to scale these services with velocity. As Warehouse and Logistics Capability Manager, you'll report to our Global Warehousing and Logistics Lead and own the design, and roll-out of key capabilities (selection of in-house or off-the-shelf tooling, process, and data integrity), implementation and integration with strategic partnerships to achieve global scale. This is a strategic role on a small team, so you'll move between building the tooling, processes, controls, and metrics that let us scale as our hardware footprint grows. You should be comfortable making decisions with incomplete information, communicating clearly with engineers and vendors alike, and holding a high bar for supply chain and logistics capabilities. Key responsibilities Define the key requirements for new capabilities in collaboration with partner teams Own the program management, selection and implementation of tools pertaining to warehouse, inventory, transport management etc., and their integration with internal and external tools Enable expansion to new geographies with the right tools, processes, SOPs and data in conjunction with the operational warehouse managers Conduct RFP where needed and drive tool selection and/or build in line with business requirements Ensure third party vendor tools are fully integrated with Anthropic’s architecture and meet compliance, and regulatory requirements Conduct full testing and effective adoption of new processes and tools, effectively managing risks and timely implementation Develop/enhance reports on operational metrics such as receiving cycle time, inventory accuracy, on-time delivery, and freight cost, and use them to drive continuous improvement Minimum qualifications Experience managing warehouse or logistics operations for physical goods, including receiving, inventory control, and outbound shipping Hands-on experience using and designing warehouse management and inventory management system, and comfort working in spreadsheets to analyze inventory and shipment data Experience managing third-party logistics providers or carriers, including negotiating service levels and holding vendors accountable to them Working knowledge of domestic freight (LTL, FTL, and parcel) and the documentation that goes with it Familiarity with safety and regulatory requirements for shipping and storing IT or electronic equipment, such as hazardous materials rules for lithium batteries Strong written and verbal communication skills, with the ability to coordinate across technical and non-technical teams and external partners Demonstrated ability to build processes from scratch and keep operations running reliably as volume and complexity increase Ability to travel to warehouse and data center sites in the US as needed Preferred qualifications Experience handling data center or enterprise IT hardware, including servers, GPUs or other accelerators, and networking equipment Experience with international freight forwarding, customs brokerage, and export control requirements such as EAR Experience with secure chain-of-custody programs, asset tagging, and data-bearing device sanitization or destruction Experience directly managing warehouse staff or contract labor Familiarity with ERP or procurement systems and how inventory data flows between them and warehouse systems Experience with Agile development and frontier AI tools Experience supporting rapid infrastructure buildouts, whether in cloud, telecom, or another hardware-intensive industry The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Design, build, and operate feedback and data collection interfaces and maintain backend services and pipelines for human-in-the-loop model training. | Strong full-stack engineering skills with production experience in TypeScript, React, and Python, project ownership, and backend service operation experience. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's RL Data Platform team builds the systems that produce, move, and serve the human data Claude learns from: the interfaces humans use to give feedback, the pipelines that turn raw feedback into training signal, and the tooling researchers use to launch, monitor, and inspect data collection. Every RL run depends on a steady supply of high-quality data - human feedback, expert demonstrations, graded transcripts - and when a researcher has an idea for new data on Monday, our job is to make it collectable by Wednesday and in the training mix by Friday. This is a full-stack, ownership-heavy role on a small, senior team. You'll design and ship web interfaces used by thousands of expert annotators, build the backend services and data pipelines behind them, and work directly with RL researchers to understand what data they need and why. You'll scope your own projects, make architectural calls, and see them through to production. We're looking for engineers who treat researchers as their users, build for reliability first, and care as much about the shape of the data leaving the system as the UI going into it. Key responsibilities Design, build, and operate the feedback and data collection interfaces used by human annotators, domain experts, and internal researchers. Build and maintain the backend services, APIs, and pipelines that route model samples to humans and return structured feedback to training. Own the reliability, latency, and usability of systems that run continuously against live model endpoints. Partner with RL researchers to translate loosely specified data needs into well-scoped collection campaigns and the tooling to run them. Build dashboards, monitoring, and inspection tools so researchers can see data quality and throughput without asking an engineer. Identify and remove the bottlenecks between "we want this data" and "it's in the training mix". Minimum qualifications Strong full-stack engineering skills, with production experience in TypeScript/React on the frontend and Python on the backend. Experience designing and operating backend services and data pipelines that other teams depend on. A track record of owning projects end-to-end, from an ambiguous brief to something in production that people use. Comfort working directly with technical stakeholders whose needs change week to week, and the judgment to push back when something isn't worth building. Effective use of AI tools in your own day-to-day work. Care about the societal impacts of your work. Preferred qualifications Experience building annotation, labelling, evaluation, or other human-in-the-loop data tooling. Experience with RLHF, preference data, or other human-feedback pipelines for ML systems. Experience shipping researcher-facing or other expert-facing internal tools people love: interviewing users, hunting down friction, measurably improving the experience. Experience running experiments on data collection interfaces and using the results to improve data quality. Experience working with crowdworker or expert vendor platforms at scale. Familiarity with how LLMs are trained and evaluated. Representative projects Build an interface that lets a domain expert review a long agentic transcript, flag the step where things went wrong, and write a corrected continuation - with the result landing in a training-ready format. Rework the sampling path between our feedback interfaces and model endpoints to cut time-to-first-sample for annotators. Build a campaign launcher that lets a researcher stand up a new data collection effort (task, rubric, population, quality checks) without writing code. Instrument annotator behaviour to detect low-effort or adversarial work and surface it to the quality team automatically. Design the data model for a kind of feedback we haven't collected before, and ship the pipeline that gets it into the training mix. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000—$405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Design, build, and maintain backend services, data pipelines, and web interfaces for RL training data collection, partnering with researchers to ensure reliability and data quality. | Strong full-stack engineering with TypeScript, React, Python, end-to-end project ownership, and experience building data pipelines or researcher-facing tools. | About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's RL Data Platform team builds the systems that produce, move, and serve the human data Claude learns from: the interfaces humans use to give feedback, the pipelines that turn raw feedback into training signal, and the tooling researchers use to launch, monitor, and inspect data collection. Every RL run depends on a steady supply of high-quality data - human feedback, expert demonstrations, graded transcripts - and when a researcher has an idea for new data on Monday, our job is to make it collectable by Wednesday and in the training mix by Friday. This is a full-stack, ownership-heavy role on a small, senior team. You'll design and ship web interfaces used by thousands of expert annotators, build the backend services and data pipelines behind them, and work directly with RL researchers to understand what data they need and why. You'll scope your own projects, make architectural calls, and see them through to production. We're looking for engineers who treat researchers as their users, build for reliability first, and care as much about the shape of the data leaving the system as the UI going into it. Key responsibilities Design, build, and operate the feedback and data collection interfaces used by human annotators, domain experts, and internal researchers. Build and maintain the backend services, APIs, and pipelines that route model samples to humans and return structured feedback to training. Own the reliability, latency, and usability of systems that run continuously against live model endpoints. Partner with RL researchers to translate loosely specified data needs into well-scoped collection campaigns and the tooling to run them. Build dashboards, monitoring, and inspection tools so researchers can see data quality and throughput without asking an engineer. Identify and remove the bottlenecks between "we want this data" and "it's in the training mix". Minimum qualifications Strong full-stack engineering skills, with production experience in TypeScript/React on the frontend and Python on the backend. Experience designing and operating backend services and data pipelines that other teams depend on. A track record of owning projects end-to-end, from an ambiguous brief to something in production that people use. Comfort working directly with technical stakeholders whose needs change week to week, and the judgment to push back when something isn't worth building. Effective use of AI tools in your own day-to-day work. Care about the societal impacts of your work. Preferred qualifications Experience building annotation, labelling, evaluation, or other human-in-the-loop data tooling. Experience with RLHF, preference data, or other human-feedback pipelines for ML systems. Experience shipping researcher-facing or other expert-facing internal tools people love: interviewing users, hunting down friction, measurably improving the experience. Experience running experiments on data collection interfaces and using the results to improve data quality. Experience working with crowdworker or expert vendor platforms at scale. Familiarity with how LLMs are trained and evaluated. Representative projects Build an interface that lets a domain expert review a long agentic transcript, flag the step where things went wrong, and write a corrected continuation - with the result landing in a training-ready format. Rework the sampling path between our feedback interfaces and model endpoints to cut time-to-first-sample for annotators. Build a campaign launcher that lets a researcher stand up a new data collection effort (task, rubric, population, quality checks) without writing code. Instrument annotator behaviour to detect low-effort or adversarial work and surface it to the quality team automatically. Design the data model for a kind of feedback we haven't collected before, and ship the pipeline that gets it into the training mix. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000—$850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.