Abnormal

You would lead infrastructure features and roadmap work while maintaining CI/CD pipelines and build systems for reliable software delivery. | The role requires 3+ years in backend or platform engineering, 2+ years of Python, and experience with cloud-native projects and production CI/CD systems. | About the Role Abnormal AI empowers businesses of all sizes to combat cybercrime through our innovative cloud products. To achieve our mission, we're building a suite of interconnected security solutions on a unified platform, designed to operate flawlessly in global data centers. The Development Infrastructure team plays a critical role in multiplying the impact of our product teams. We create an environment that fosters high-quality software development, and engineering excellence. This team has become instrumental in the success of our engineering organization. You are someone who: Thrives in a collaborative, fast-paced environment Possesses a passion for helping others build world-class systems Demonstrates exceptional teamwork skills Embraces continuous learning and enjoys tackling complex problems What you will do Lead the design and delivery of complex, multi-component features and systems of the Development Infrastructure team's offerings, and shape the roadmap for this area. Develop and maintain CI/CD infrastructure and tools for Engineering to develop and ship their changes reliably with less effort. Design and implement enhancements to GHA infrastructure, base Docker images and build/deploy pipelines with improvements in scalability, performance and costs. Use AI tools to explore and compare solutions, and adapt the generated changes to real production constraints, weighing system complexity and long-term maintainability. Take ownership of on-call issues, including complex issues where the root cause is unclear, and fix the systemic gaps behind them. Participate in planning, code reviews, standups, and other aspects of the software development life cycle, and coach other engineers on the team. Must Haves 3+ years of professional experience as a hands-on engineer building backend systems and/or platforms. 2+ years of experience working with Python. Experience delivering complex projects end-to-end in a cloud native environment. Experience building or operating CI/CD, build, or deployment systems in production, including on-call and incident response. Understanding of distributed systems, containerization and microservices. Practical experience using Generative AI tools in day-to-day engineering workflows. Nice to Haves Experience creating and maintaining CI/CD systems. Experience with GitHub Actions. Experience with Go. Experience with Bazel. Experience working on or with teams like “Engineering Effectiveness”, “Engineering Productivity”, “Development Experience”, “Development Infrastructure” or similar. Knowledge of Docker, Kubernetes, or similar technologies. Familiarity with Generative AI tools such as Codex and Claude, and experience driving AI-first workflows and solutions. #LI-ML1 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $149,200—$214,500 USD A note on AI in our process: Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Translate revenue and pipeline targets into demand generation strategies and execution roadmaps, while partnering with marketing leadership to improve lead lifecycle and funnel conversion. | Requires 7+ years in demand generation, marketing operations, or revenue operations within a high-growth B2B SaaS company, plus strong analytical and cross-functional alignment skills. | About the Role Every closed-won deal starts as a signal. Your job is to make sure none of them get lost. As Senior Manager, Demand Generation Operations, you'll be the strategic business partner to Abnormal's Revenue Marketing and Digital Marketing leaders, and the person who connects marketing activity to revenue outcomes. Reporting to Ted Noble, VP of GTM Operations, you'll translate ARR and pipeline targets into operational demand generation strategies and execution roadmaps, then ensure we are exceeding our plan for full funnel from MQL to Closed Won. When conversion stalls, a handoff breaks, or a stage gets stuck, you'll find out why and fix it. This is a role for someone who is energized by funnel math, cross-functional alignment, and turning messy data into clear decisions, and who wants to help make Abnormal the #1 AI-native company. The targets are ambitious because the momentum is real. Abnormal closed FY26 at roughly $380M in ARR, growing about 50% year over year, with more than 5,000 customers and over 30% of the Fortune 500 trusting us to protect their people. As we expand from email security into the Abnormal Behavioral AI platform, the funnel gets more complex: more products, more buying committees, and more paths from first touch to closed-won. Hitting our growth goals depends on a demand engine that is measured clearly, managed tightly, and improved every quarter. You'll build and run that engine. What You Will Do Turn targets into plans. Translate ARR and pipeline targets into operational demand generation strategies, funnel models, and execution roadmaps, working back from revenue goals to the volume, conversion, and velocity needed at every stage. Be the strategic partner to marketing leadership. Serve as the operational business partner to the leaders of Revenue Marketing and Digital Marketing, helping them plan, prioritize, and invest where the funnel says it will matter most. Own the lead lifecycle model. Establish and refine the end-to-end lead lifecycle model (MQL, GP, SAL, QP, POV, Closed Won), conversion benchmarks, and Sales-Marketing Service Level Agreements (SLAs). Run the funnel reviews. Lead regular pipeline velocity and campaign performance reviews with Sales, Business Development (BDR/SDR), and Marketing executives to identify funnel bottlenecks and optimize conversion paths. Solve bottlenecks from MQL to Closed Won. Diagnose where and why pipeline stalls, whether in lead quality, speed-to-lead, handoffs, stage progression, or win rates, and drive the fixes with the teams that own them. Hold the line on SLAs. Monitor SLA adherence and stage latency across Marketing, SDR, and Sales teams, and make performance visible so accountability is shared and gaps get closed quickly. Connect programs to pipeline. Partner with Marketing Operations and Revenue Analytics to measure campaign and channel performance against pipeline and revenue, so investment decisions are grounded in real outcomes. Plan for a multi-product funnel. Help evolve the funnel model, targeting, and account-based planning as we sell more products into more buying committees across the platform. Use AI to see problems sooner. Bring an AI-first mindset to funnel monitoring, using automation and AI-driven insights to surface early warning signs and recommended actions before they become missed quarters. Partner across GTM. Work closely with Marketing Operations, Sales Operations, Revenue Systems & Analytics, Sales, and SDR leadership so systems, definitions, and reporting stay aligned across the funnel. Must Haves 7+ years of experience in demand generation operations, marketing operations, revenue operations, or a related analytical GTM role at a high-growth B2B SaaS company. Proven track record translating revenue and pipeline targets into demand generation plans and funnel models. Deep experience designing and managing lead lifecycle models, stage definitions, conversion benchmarks, and Sales-Marketing SLAs. Experience leading pipeline and campaign performance reviews with senior Sales and Marketing leaders, and driving action from the findings. Strong analytical skills and comfort working with funnel, attribution, and pipeline data across Salesforce, marketing automation, and BI tools. Working knowledge of lead scoring, routing, and marketing attribution, and how they affect funnel performance. Exceptional cross-functional communication skills, with the credibility to align Marketing, SDR, and Sales leaders around shared definitions and goals. Nice to Haves Experience with tools in our ecosystem, such as Salesforce, Marketo, 6sense, Snowflake, and Sigma. Experience supporting account-based marketing and multi-product or platform GTM motions. Background in cybersecurity or another technical, enterprise-focused category. #LI-ML2 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $153,000—$220,000 USD A note on AI in our process: Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

You would lead deal strategy and deal desk operations, structure enterprise deals, enforce commercial policies, and build AI-enabled quoting and approval workflows. | The role requires 8+ years in deal desk, revenue operations, or commercial finance, leadership experience, and deep expertise in SaaS deal economics and Salesforce CPQ. | About the Role The best deals don't happen by accident. They're designed. As Director, Deal Strategy & Operations, you'll build and lead the function that shapes how Abnormal structures, approves, and closes its most important enterprise deals. Reporting to Ted Noble, VP of GTM Operations, you'll own two connected capabilities. The first is Deal Strategy, where you'll partner with sellers and leadership to design commercial structures for high-value enterprise customers that meet what the customer needs and stay within the guardrails that keep our business healthy. The second is Deal Desk, where you'll run the day-to-day engine of deal intake, approvals, non-standard terms, and related CRM data quality. This is a builder's role for someone who wants to help make Abnormal the #1 AI-native company: you'll take an AI-first approach to quoting, field guidance, approvals, and policy, so the field gets fast, confident answers and the business gets consistent, well-governed deals. The opportunity is growing quickly. Abnormal closed FY26 at roughly $380M in ARR, growing about 50% year over year, with more than 5,000 customers and over 30% of the Fortune 500 trusting us to protect their people. As we expand from email security into a broader behavioral AI platform, our deals are getting bigger and more complex: multi-product bundles, enterprise license agreements, and multi-year structures. You'll make sure every one of those deals is built to win today and to grow with the customer over time. What You Will Do Lead Deal Strategy for strategic enterprise deals. Partner with Account Executives, sales leaders, and executives to design commercial structures for high-value opportunities, including multi-product bundles, enterprise license agreements, multi-year terms, and expansion and renewals. Balance customer needs with business guardrails. Translate what customers are asking for into structures that protect margin, revenue quality, and long-term value, and bring clear recommendations to leadership when a deal needs an exception. Own Deal Desk operations. Run day-to-day deal intake and approvals, keeping deals moving quickly through the right reviewers with clear service levels, especially at quarter close. Validate non-standard terms. Review and resolve non-standard pricing, payment, billing, and contractual requests, working closely with Finance, Order Management and Legal to apply policy consistently. Make CRM data trustworthy. Ensure deal approvals, business justifications, and associated data in Salesforce is accurate and complete. Build AI-first deal systems. Design how AI and agentic workflows support quoting, field guidance, deal approvals, and policy questions, so sellers can self-serve routine answers and your team can focus on the deals that need human judgment. Set the standard that AI speeds things up without weakening accuracy, auditability, or policy compliance. Shape the future of quoting. Partner with Revenue Systems on the design of our next-generation quoting and approval experience, including CPQ, approval workflows, and pricing and packaging changes as new products launch. Write and maintain deal policy. Own the playbooks, approval matrices, and deal guidelines that the field relies on, and keep them current as our products, pricing, and markets evolve. Enable the field. Equip sellers and sales leaders with the guidance, tools, and training to structure better deals on their own, across every region and segment using an AI first approach. Build and lead the team. Hire, develop, and lead a high-performing team of deal strategy and deal desk professionals, with a focus on scaling through systems rather than headcount alone. Be a trusted cross-functional partner. Work hand in hand with Sales, Finance, Legal, Revenue Systems, Product, and Order Management to keep the full deal lifecycle connected from first quote to booked revenue. Must Haves 8+ years of experience in deal desk, deal strategy, revenue operations, or commercial finance at a high-growth B2B SaaS company, with at least 3 years leading teams. Proven track record structuring complex enterprise deals, including multi-product, multi-year, and enterprise license agreements, in the six- and seven-figure ARR range. Deep understanding of SaaS deal economics, including discounting, pricing and packaging, payment terms, bookings policy, and the revenue recognition implications of different structures. Hands-on experience with Salesforce and CPQ quoting and approval workflows, plus a strong commitment to CRM data quality. Experience designing or rebuilding deal approval processes, policies, and service levels that hold up at scale and under quarter-end pressure. Demonstrated experience applying AI and automation to deal workflows, with sound judgment about where it helps and where human review is required. Strong partnership with Finance, Order Management and Legal, and the credibility to influence senior sales leaders and say no constructively when a deal doesn't fit. Exceptional communication skills, with the ability to turn complex commercial tradeoffs into clear recommendations. Nice to Haves Experience with tools in our ecosystem, such as SpotDraft, Maxio, NetSuite, Gong, Snowflake, and Sigma. Experience leading or contributing to a CPQ implementation or replacement. Background in cybersecurity or another technical, enterprise-focused category. Experience supporting global deal operations across EMEA and APJ. #LI-ML2 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $204,000—$240,000 USD A note on AI in our process: Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Lead and scale security teams, represent security as the CISO’s deputy, and own the security engineering roadmap across cloud architecture, detection and response, and secure platform investments. | Requires 10+ years in security or software engineering, at least four years in management, and strong software engineering and cloud-native expertise including AWS and Kubernetes. | About the Role Abnormal AI protects organizations from the most sophisticated email and collaboration attacks using behavioral AI. Security is not a bolt-on at Abnormal; it is core to the product we sell and the trust our customers place in us. Our security organization operates a commercial cloud environment and a separate FedRAMP-authorized environment, and we are pursuing increasingly rigorous federal authorizations as we grow. We are hiring a Director of Security reporting to the CISO and leading the Security Engineering organization. You will build and scale high-performing security teams, own major security programs end to end, and operate autonomously in the CISO's absence, including representing security to executive leadership, customers, and auditors. This is a role for a deeply technical leader with a software engineering background who has grown into people leadership. You have built security teams from the ground up, you write and review code and architecture when it matters, and you believe the best security organizations earn their influence through partnership rather than policy enforcement. Our Security Philosophy We run security the way the best engineering-led companies do: Security reduces toil. Our job is to make the rest of the company faster and safer at the same time. If a control adds friction without reducing risk, it is a defect. Paved paths, safe by default. We invest in guardrails, golden paths, and secure-by-default infrastructure so the easy choice is the secure choice. We prefer preventing classes of problems over chasing individual findings. Partnership over gatekeeping. Security succeeds only through deep collaboration with engineering, IT, and business teams. We embed with builders, we ship alongside them, and we take on their constraints as our own. Engineering-grade rigor. We treat security problems as engineering problems: automated, measurable, code-reviewed, and continuously improved. If the security cultures that value freedom and responsibility, context over control, and guardrails over gates resonate with you, you will feel at home here. What You Will Do Serve as deputy to the CISO: act with full authority in the CISO's absence and represent the security organization to executives, customers, and regulators. Lead, coach, and grow managers and senior engineers across Security Engineering and Security Operations. Own the security engineering roadmap: cloud security architecture (AWS-first), detection and response, identity, vulnerability management, and secure-by-default platform investments. Drive cross-functional programs with Engineering, IT, and Product, from AI security governance to data perimeter controls to federal compliance initiatives. Set and defend engineering standards for the security organization: everything as code, automated where possible, measured against outcomes rather than activity. Build hiring pipelines and raise the bar on every hire; own performance management, promotion cases, and succession planning within your teams. Translate technical risk into business terms for the executive team and board, and translate business priorities into a coherent security strategy. Must Haves 10+ years in security or software engineering, including 4+ years managing security teams, ideally including managers of managers or equivalent scope. A genuine software engineering background: you have shipped production software, and you evaluate security solutions the way an engineer would. A proven record of building and scaling high-performing security teams, with alumni who would work for you again. Deep technical fluency in cloud-native environments: AWS organizations and multi-account governance, Kubernetes, identity and access, detection engineering, and modern SDLC security. Demonstrated cross-functional leadership: you have earned the trust of engineering leaders and shipped security outcomes through their teams, not around them. Strong written communication: you produce decision-ready documents and can drive alignment asynchronously. Executive presence: comfortable presenting to C-level leadership, customers, and auditors without preparation from the CISO. Strong Signals You are currently a security engineering manager or senior manager at a fintech, high-growth startup, or forward-leaning enterprise, and you are ready for broader scope. You have built paved-path or secure-by-default platforms that measurably reduced both risk and developer friction. Experience with compliance-driven environments (FedRAMP, SOC 2, ISO 27001) without letting compliance define the security program. Experience securing AI/ML systems or governing AI adoption at scale. You have operated in environments where security headcount was scarce and automation was the only way to scale. Why This Role You will inherit strong teams, an executive staff that treats security as a first-class function, and a CISO who wants a true partner rather than a lieutenant. The scope is broad, the autonomy is real, and the ceiling on this role is defined by what you take on. #LI-ML1 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $214,200—$308,000 USD A note on AI in our process: Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Architect and maintain model serving infrastructure and real-time streaming pipelines while mentoring junior engineers. | 5+ years in software engineering focused on ML-engineering, distributed systems, and cloud platforms. | About the Role Abnormal AI is looking for a Senior Software Engineer to join the Detection Team. The Detection Division is focused on building the world’s most advanced technology for identifying and stopping email and cloud-based attacks that were previously undetectable and helping make the world a safer place. As a Senior Software Engineer building systems for Detection’s Signals and Serving Team, you will make feature development at Abnormal fast, responsive, stable, and confident for our ML and Data Science team. The ideal candidate would have the following qualities: A first principles approach to building scalable, customer-centric solutions A drive to solve meaningful & pragmatic problems for real-world people An ownership and impact-oriented outlook on your efforts and growth An ability to iterate in real-time-solving novel problems, quickly and autonomously An ability to iterate in real-time - solving novel problems, quickly and autonomously What you will do Architect, design, build, deploy, and maintain Model Serving infrastructure that supports a world-class Detection Engine Own projects that scale our model serving and data processing services to handle 10x the traffic we serve today Build the platform for fighting against rapidly generated AI attacks Own real-time, near real-time streaming pipelines, and online feature serving services Build Abnormal’s ML Training platform, improving MLE velocity and product precision and recall Collaborate closely with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing Coach and mentor junior engineers via 1on1s, pair programming, high-quality code reviews, and design reviews Must Haves 5+ years of experience as a Software Engineer or in a similar role, with hands-on experience in building ML-engineering focused solutions. Experience maintaining large-scale distributed systems on cloud platforms such as AWS, GCP, or Azure, including a strong grasp of cloud-based engineering best practices. Experience with maintaining real-time and near real-time data pipelines or streaming services at high scale Proven ability to collaborate effectively with cross-functional teams, including data scientists, machine learning engineers, product managers, and other stakeholders. You can translate requirements into actionable technical tasks, communicate progress clearly, and adapt to feedback. Excellent problem-solving skills and the ability to work independently in a fast-paced environment. You can break down complex challenges into manageable steps and iterate on solutions, balancing immediate needs with long-term scalability. Familiarity with machine learning workflows and requirements to support MLE teams effectively. This includes feature development and serving at 50K+ QPS, offline/online equivalency, large batch jobs for data gathering and training of tree and deep learning models. Experience with streaming data architectures and real-time processing. Knowledge of security and compliance frameworks as they relate to data engineering and data privacy. #LI-PP1 A note on AI in our process: Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Lead regional field and partner marketing strategies to drive pipeline growth and revenue through integrated marketing programs and collaboration with sales teams. | At least 7 years B2B marketing experience with proven field and channel marketing success, proficiency in Salesforce, Marketo, marketing analytics, and strong strategic and communication skills. | About the Role Abnormal AI is seeking a strategic and experienced Senior Revenue Marketing Manager to lead regional marketing initiatives that drive pipeline growth across our Enterprise and Strategic business in the TOLA region. This role owns the end-to-end planning, execution, and performance of integrated marketing programs in close partnership with sales and channel teams. You will lead field and partner marketing strategy for your assigned region, creating high-impact campaigns, tailoring messaging for local relevance, and reporting on results tied to bookings and qualified pipeline. This is a highly visible role that requires marketing leadership, strong cross-functional collaboration, and a deep understanding of B2B sales motions. You thrive in fast-paced, high-growth environments and have a passion for translating strategy into execution. What You Will Do Lead regional field and partner marketing strategy to support pipeline and revenue goals through campaigns, events, ABM programs, and digital amplification Own end-to-end execution of region-specific initiatives—from idea through reporting—with accountability for budget, timeline, and impact Collaborate closely with AEs, CAMs, SDRs, and partner managers to drive aligned execution, participation, and adoption of marketing programs Build and maintain a quarterly pipeline generation plan, forecast impact, and adjust tactics based on results and market feedback Customize corporate messaging and content to suit regional buyer personas and go-to-market strategies Report on performance using Salesforce, Marketo, and Sigma dashboards; deliver insights to sales and marketing leadership to optimize ROI Mentor junior marketing team members or contribute to cross-regional initiatives that raise the bar for marketing excellence Must Have 7+ years of B2B marketing experience, including field and channel marketing, with a strong track record of pipeline contribution Proven ability to independently plan, lead, and measure marketing programs tied to regional sales goals Deep experience collaborating with sales, partners, and cross-functional stakeholders to influence outcomes Strong strategic thinking, with hands-on ability to execute campaigns and adapt in real time Excellent written and verbal communication skills with the ability to tailor messaging to different audiences Proficiency with Salesforce, Marketo, and marketing analytics tools Willingness to travel 20–25% as needed Nice to Have Cybersecurity or SaaS industry experience Familiarity with account-based marketing (ABM) strategies Experience managing partner co-marketing initiatives or working within an ecosystem of distributors and system integrators Bachelor’s degree in Marketing, Business, Communications, or a related field #LI-ML2 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $133,900—$192,500 USD A note on AI in our process: Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Build identity verification and fraud detection systems analyzing real-time data to prevent malicious actors. | At least 2 years experience in software development, productionizing large-scale data systems, bachelor's degree, and strong debugging skills. | About the Role As organizations face increasingly sophisticated social engineering and insider threats, the very foundation of trust—the employee identity—is under attack. Abnormal’s Identity Security team is building a groundbreaking product to detect and prevent fraudulent employee identities, specifically targeting high-stakes threats like infiltrators seeking to funnel funds through deceptive employment. We use advanced behavioral intelligence to scrutinize candidate details—from resumes and application metadata like IP addresses, email addresses, and phone numbers—to identify suspicious patterns and prevent malicious actors from entering the workforce. We are extending Abnormal’s leadership in AI-native security to protect the integrity of the modern enterprise at the point of hire. What you will do Build identity verification and fraud detection systems to scrutinize candidate data during the application process. Develop sophisticated correlation engines that match candidate details (IPs, phone numbers, email history, resume metadata) against known indicators of fraudulent or state-sponsored activity. Create high-availability pipelines that ingest and analyze signals from application tracking systems (ATS), identity providers, and external risk intelligence. Ship automated guardrails that flag high-risk candidates in real-time, enabling security teams to act before an infiltrator is onboarded. Drive 0→1 iteration: prototype quickly, test fraud detection assumptions, learn from emerging threat patterns, and scale simple, effective solutions. Collaborate across security, platform, and data teams; write and review technical designs; and participate in core SDLC rituals. Must Haves 2+ years building software applications. Experience productionizing large-scale, data-intensive systems. High velocity and creativity in solving technical challenges related to fraud detection and pattern matching. Experience & desire to adopt & improve AI-native development workflows. Strong debugging skills with logs, metrics, and behavioral signals. Ability to translate complex security and business requirements into high-quality software. Ability to independently solve complex problems and work cross-functionally. BS in CS/SE/IS or a related field. Nice to Have Experience with Go and Python. Experience in fraud detection, identity verification, or anti-money laundering (AML) systems. Background in cybersecurity, specifically focused on insider threats or nation-state actor TTPs (Tactics, Techniques, and Procedures). Experience with big data, statistics, and ML for identity/behavioral risk modeling and anomaly detection. #LI-NT1 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $149,200—$214,500 USD A note on AI in our process: Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Lead security architecture and threat modeling for AWS cloud environments and mentor teams on security standards. | Proven cloud-native security engineering experience with AWS and proficiency in Python or Go. | About the Role Abnormal AI is looking for a Senior Cyber Security Engineer to help build the next generation of security capabilities at scale. This is a senior IC-level role that blends deep security expertise with the judgment to direct AI tools effectively — you'll increasingly rely on AI to scaffold Terraform modules, prototype detection logic, and draft integrations, while you own the architecture decisions, validate what ships, and catch the failure modes AI won't flag on its own (overprivileged roles, missed edge cases, subtle logic gaps). As a technical lead, you will own the architecture and correctness of systems that enhance both preventative guardrails and detective capabilities across our primarily AWS-based cloud environment, partnering closely with both platform engineering and product teams on security architecture reviews. You'll raise the AI leverage of the engineers around you — not by teaching scripting basics, but by turning your review judgment into reusable standards the team can build on directly. You'll act as a technical liaison across teams and contribute directly to keeping our platforms and customers secure. This is a role for engineers who are intellectually curious and motivated to bridge security principles, engineering execution, and AI-accelerated delivery. Who you are An intellectually curious, solution-focused engineer with a security mindset who thrives in fast-paced environments A technical leader who can architect scalable security solutions while maintaining engineering velocity — increasingly by directing AI to do the first draft and applying judgment to the result Someone who thinks like an attacker but builds like a defender, and who treats AI-generated infrastructure and detection logic with the same scrutiny as a junior engineer's first PR Someone with high agency who proactively spots what in their own workflow (and the team's) AI can absorb, and actually builds the automation to make that real — not someone waiting to be told A collaborative engineer who can translate security requirements into actionable engineering tasks A mentor who scales their judgment across the team — reviewing AI-generated code and infra for security gaps, and encoding what they learn into reusable playbooks and standards rather than repeating the same feedback one engineer at a time What you will do Lead threat modeling and security design discussions with both platform and product teams, translating risks into engineering actions and using AI to rapidly stress-test designs against attack scenarios before committing engineering time to a direction. Partner with product engineering to review the security architecture of new product features — assessing designs for data exposure, access control, and abuse-case risk before they ship — using AI to speed up first-pass analysis so your review time goes toward the highest-risk decisions. Collaborate with Platform, Infra, and DevOps teams to build scalable preventative controls in AWS via Infrastructure-as-Code — using AI coding agents to scaffold and iterate on Terraform/CloudFormation modules, reserving your own time for least-privilege review, blast-radius analysis, and edge cases. Evaluate and uplift security tooling across commercial, cloud-native, and AI-assisted capabilities, focusing on scale, efficiency, and precision. Mentor engineers on how to get real leverage from AI — reviewing AI-generated code and infrastructure together, and turning recurring feedback into standards and reusable playbooks instead of repeating it review after review. Use AI to rapidly prototype automation for signal correlation, alert enrichment, and auto-remediation of known failure patterns, then harden and productionize what proves out rather than hand-building every workflow from a blank file. Architect, build, and validate integrations between AWS and other cloud-native infrastructure and security tooling (e.g., SIEM, SOAR, IAM tooling), with a growing share of first-draft code AI-generated and human-owned. Serve as a hands-on technical contributor during security incidents, using AI to accelerate log and telemetry triage while owning the judgment calls that determine root cause and response. Build and maintain reusable AI-assisted playbooks (for IaC security review, detection authoring, alert triage) that scale your judgment across the security and platform teams. Must Haves Proven delivery in security engineering or infrastructure security roles, ideally in cloud-native environments. Deep comprehension of native AWS architecture services and identity/access patterns — IAM, STS, cross-account roles and resource policies, VPC and network segmentation, KMS — with AWS as our primary cloud platform, plus working knowledge of Azure and GCP. Strong scripting and dev fundamentals in Python and/or Go — enough to read, critique, and confidently modify AI-generated code, not just prompt for it; proficiency with Git, Linux, and infrastructure automation patterns. Demonstrated fluency directing AI coding/agent tools (e.g., Claude Code, Cursor, Copilot) to accelerate delivery, paired with the judgment to catch when AI-generated infrastructure or security logic is wrong, incomplete, or dangerous. Expertise in integrating or building tooling for SIEM, SOAR, vulnerability management, and CSPM platforms. Experience deploying security controls via Infrastructure-as-Code (Terraform or CloudFormation), primarily in AWS. Comfortable investigating logs, tracing events, and contributing to incident analysis workflows. Proven ability to influence and collaborate cross-functionally with engineering, infra, product, and IT. Strong written communication and documentation skills and being able to convey complex designs clearly. Background with using and securing container orchestration (Kubernetes), including workload security and service mesh controls. Nice to Have Experience working in fast-paced or startup environments with sometimes ambiguous ownership lines. Experience building or operating agentic workflows/AI tooling for security use cases (detection authoring, alert triage, IaC generation/review). Familiarity with JavaScript or TypeScript, particularly in the context of DevOps tooling or plugins. Hands-on experience with commercial Cloud Security tools (CNAPP, CSPM, DSPM, KSPM) Partner with cloud infrastructure teams to implement and maintain security controls across AWS accounts and services. Prior experience building security telemetry pipelines or log correlation frameworks. Exposure to compliance frameworks (SOC 2, ISO 27001) and how engineering decisions affect auditability. Familiarity with CI/CD systems and integrating security checks into developer workflows. #LI-PP1 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $153,000—$220,000 USD A note on AI in our process: Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore. They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Design and maintain scalable backend services and collaborate with teams to ensure system reliability. | Bachelor's degree and 3+ years backend and distributed systems experience with proficiency in Go or Python. | About the Role Abnormal AI is seeking a Software Engineer to join the Message Mailflow team. The Message Mailflow team is responsible for building and maintaining stable, efficient, and hands-off systems that power the ingestion of billions of emails per day. Our systems are the backbone of Abnormal's core Inbound Email Security product—handling everything from upstream mailbox monitoring and email notifications to downstream remediation actions on malicious messages. The Message Mailflow team develops and manages tier 0 backend services that are mission-critical to Abnormal's success, including but not limited to Subscription Manager (which mailboxes we monitor), Notification Producer (processing new email notifications from providers), and Remediation (executing actions on malicious messages). This is a backend and systems-heavy team, and the ideal candidate will have experience working with distributed systems at scale and a passion for operational excellence. The ideal candidate has strong backend and distributed systems experience, a deep appreciation for email infrastructure, and the ability to thrive in a fast-moving 0-to-1 build environment. What You Will Do Design & execute software projects that are critical to Abnormal's core product, working with a team of engineers through conception, design, implementation, launch, and operation Own and improve the stability, performance, and scalability of tier 0 backend services that process billions of emails daily Collaborate with teams across R&D including Detection, Products, and Infrastructure to ensure Message Mailflow services meet the needs of the broader organization Participate in oncall rotations to maintain the reliability and uptime of mission-critical systems Drive continuous improvement by identifying opportunities to enhance system efficiency, reduce operational overhead, and increase reliability Raise the bar of engineering excellence, actively contributing to knowledge sharing within the team and participating in professional development activities Must Haves BS degree in Computer Science, Applied Sciences, Information Systems or other related engineering field 3+ years of industry experience on backend software development & distributed systems, designing & building software applications Experience with our stack: Go and/or Python Experience working with distributed teams, proficient in asynchronous and written communication Experience building features & components from scratch and operating them, balancing feature development work with operational tasks Open to following pre-established guidelines, coding practices, and conventions You’re growth-driven & looking to increase impact & responsibility over time Nice to Have Experience with our stack: AWS, K8, Django, Spark, Prometheus Familiarity with AWS services and deployment practices. Knowledge of containerization using Docker or similar technologies. #LI-PP1 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $149,200—$214,500 USD AI and our hiring process Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and identify areas for the interviewer to explore. They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Build and maintain secure, AI-enabled workforce technology across identity, endpoints, and SaaS platforms with automation and self-service improvements. | At least 2 years IT engineering or systems administration experience with proficiency in identity and device management, strong scripting, API integration, and AI-forward mindset. | About the Role The Enterprise Platform Engineer helps build and run secure, reliable, and increasingly AI-enabled workforce technology across identity, endpoints, SaaS, collaboration, network, and office IT. You will turn policies, runbooks, telemetry, and employee needs into practical automations and self-service experiences that reduce manual work and improve the employee experience. You will work closely with experienced engineers and cross-functional partners while building ownership of defined platform capabilities and connected systems. You will use AI tools as part of your day-to-day engineering workflow and develop an AI-forward mindset grounded in security, observability, thoughtful evaluation, and human judgment. This role reflects Abnormal's VOICE values. You move with velocity, design for long-term ownership and governance, use data with intellectual honesty, stay close to customer needs, and aim for excellence in reliability and simplicity. What you will do Build and support automations for joiner, mover, and leaver flows, access requests, device management, deprovisioning, and common employee IT needs. Support identity and access capabilities using SSO, MFA, least privilege, birthright access, directory and group models, standards-based provisioning, and device trust. Help operate zero-touch device provisioning and management for macOS and Windows, including application packaging, patch automation, policy compliance, and drift detection. Use AI tools, APIs, workflows, and event-driven patterns to improve platform operations while applying appropriate access controls, approvals, and human review. Create self-service experiences, runbooks, and enablement content so employees and support teams can resolve common IT needs without escalation. Add telemetry, logging, dashboards, and basic evaluation so automations and AI-assisted workflows can be tested, monitored, debugged, and improved. Participate in Tier 2/3 incidents for assigned areas, perform root cause analysis, and feed incident learnings back into automations, runbooks, and standards. Partner with Security, GRC, People, Finance, IT Service Delivery, and platform owners to deliver changes safely and improve the employee experience. AI Forward Hiring We expect every engineer to use AI tools thoughtfully in their day-to-day work and to look for practical opportunities to improve platform reliability, speed, and employee experience. Candidates should be able to describe how they have used AI-assisted development, troubleshooting, documentation, workflow design, or analysis, and how they validated the output. Candidates should also demonstrate sound judgment about security, privacy, access control, data quality, hallucination risk, human approval, logging, and evaluation. Hands-on experience building an AI agent is not required, but curiosity, practical experimentation, and an AI-forward mindset are expected. Must Haves 2+ years of experience in IT engineering, platform engineering, systems administration, or a similar role supporting business-critical technology. Working knowledge of identity and access concepts including SSO, MFA, least privilege, directory and group management, and standards-based provisioning. Experience supporting macOS and/or Windows using modern device management approaches, with familiarity with application packaging, patching, configuration baselines, or compliance reporting. Ability to script and integrate systems using APIs, webhooks, workflow orchestration, or similar automation techniques. Familiarity with SaaS administration, collaboration tools, and employee-facing technology platforms. Experience with incident and change management, troubleshooting, root cause analysis, and documented follow-through. Clear written and verbal communication, including the ability to document technical processes and explain complex systems to technical and non-technical audiences. Nice to Have Experience in remote-first, SaaS-first, or zero-trust environments. Exposure to collaboration suites, meeting platforms, knowledge tools, room systems, or office networking. Familiarity with REST APIs, event-driven integrations, configuration-as-code, version control, or CI/CD practices for platform automations. Experience building self-service workflows or using AI tools to improve support, troubleshooting, documentation, or operational analysis. Awareness of security and compliance frameworks as applied to end-user platforms, identity, AI systems, or data governance. #LI-PP1 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $118,600—$170,500 USD AI and our hiring process Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and identify areas for the interviewer to explore. They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Architect, build, and maintain model serving infrastructure and real-time data pipelines to support detection engine and collaborate with ML and data science teams. | 4+ years software engineering experience in data-intensive, cloud-based distributed architectures with a bachelor's degree in computer science or related field. | About the Role Abnormal AI is looking for a Software Engineer II to join the Detection Team. The Detection Division is focused on building the world’s most advanced technology to identify and stop email and cloud-based attacks that were previously undetectable, helping make the world a safer place. As a Software Engineer focused on building systems for Detection’s Model Platform, you will be responsible for making feature development at Abnormal a fast, responsive, stable, and confident experience for our ML and Data Science teams. The ideal candidate brings a first-principles approach to building scalable, customer-centric solutions, an ownership-oriented mindset, and the ability to iterate quickly and autonomously on novel problems. What You Will Do Leverage industry-standard AI tools to architect, design, build, deploy, and maintain Model Serving infrastructure that supports a world-class Detection Engine. Own projects that scale our model serving and data processing services to handle 10x the traffic we serve today. Own real-time and near real-time streaming pipelines, and online feature serving services. Collaborate closely with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing. Must Haves 4+ years of experience as a Software Engineer or in a similar role, with hands-on experience building data-focused solutions. Proficiency leveraging AI tools to accelerate engineering outcomes through discovery, design, implementation, and rollout of software systems. Experience maintaining large-scale distributed systems on cloud platforms such as AWS, GCP, or Azure, including a strong grasp of best practices in cloud-based engineering. Experience with real-time and near real-time data pipelines or streaming services. Strong fundamentals in computer science, data structures, and performance optimization. BS degree in Computer Science, Applied Sciences, Information Systems, or other related engineering field. Nice to Have Familiarity with our stack: AWS, Kubernetes, Python/Django, Golang, and Postgres. Experience building scalable, enterprise-grade applications. Experience with web security (e.g., OWASP Top 10). Familiarity with AI development tools such as Cursor, GitHub Copilot, or Claude. #LI-PP1 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $149,200—$214,500 USD AI and our hiring process Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and identify areas for the interviewer to explore. They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

Lead technical direction and build foundational components for an identity security platform while collaborating with engineers and customers. | At least 5 years software engineering experience, proficiency in Python or Go, and ability to work onsite in Bay Area. | Senior Software Engineer - Identity Security Enterprises are undergoing two simultaneous transformations: moving critical infrastructure to the cloud and adopting AI agents at scale. Both create an identity explosion—humans, service accounts, and AI agents now outnumber traditional users 10-to-1, each with permissions that legacy tools can't govern. Abnormal's Identity Security team is building the platform to secure this new reality: unified visibility across all identity types, behavioral intelligence that understands what's normal, and AI-native automation that operates at cloud speed. We're extending the same behavioral approach that made Abnormal the leader in email security to protect identities across cloud infrastructure and AI systems. The Identity Security team is looking for a Senior Software Engineer to build this critical product area. You'll start hands-on with a small team, shipping code while growing the product toward market fit. What you will do Work in a team 8-10 engineers, writing and reviewing code daily alongside them Collaborate closely on technical direction while building the foundations for a scalable product Partner directly with internal and external customers to gather feedback and iterate quickly Grow the team and product as we find traction and expand scope Set engineering standards and practices that will scale as the team grows This Role Is a Fit If You Thrive in ambiguity and can guide a small team through uncertainty toward product-market fit Have strong instincts for what customers need and how to translate that into product decisions Enjoy the founding-team dynamic: small group, high ownership, fast iteration This Role Is Not a Fit If You Prefer working on established teams with well-defined roadmaps Are uncomfortable with the ambiguity of an early-stage product still finding its footing Must Haves 5+ years of software engineering experience Track record of shipping products in fast-moving environments Ability to read, write, and review code at a high level (Python/Go preferred) Experience hiring and developing engineers Bay Area location required—we operate with 25% in-office presence Nice to Have Experience building enterprise/B2B security products Familiarity with machine learning systems or ML-adjacent infrastructure Exposure to AWS, Kafka, containerized services, microservices Growth Paths Expand scope as Identity Security grows, taking on additional product lines Build out a larger team as we scale beyond initial product-market fit What We Offer The opportunity to join a veteran team that has built enduring ML platforms at Google, Twitter, Pinterest, Amazon, Microsoft, and Expanse. Our customer base includes multiple Fortune 500 companies, and Identity Security is a critical bet for Abnormal's future. #LI-NT1 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $179,800—$258,500 USD AI and our hiring process Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and identify areas for the interviewer to explore. They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.