TetraScience

Design and maintain cloud-native platforms and MLOps pipelines to support scalable AI and data workloads. | Requires 7+ years in software and infrastructure engineering with expert Python and TypeScript and production experience in Databricks MLFlow, AWS, and containerization. | About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you. What You will Do We’re looking for a Senior AI Platform Engineer to help design, build, and scale our AI and data infrastructure. In this role, you’ll focus on architecting and maintaining cloud-based MLOps pipelines to enable scalable, reliable, and production-grade AI/ML workflows, working closely with AI engineers, data engineers, and platform teams. Your expertise in building and operating modern cloud-native infrastructure will help enable world-class AI capabilities across the organization. If you are passionate about building robust AI infrastructure, enabling rapid experimentation, and supporting production-scale AI workloads, we’d love to talk to you. Design, implement, and maintain cloud-native platform to support AI and data workloads, with a focus on AI and data platforms such as Databricks and AWS Bedrock. Build and manage scalable data pipelines to ingest, transform, and serve data for ML and analytics. Develop infrastructure-as-code using tools like Cloudformation, AWS CDK to ensure repeatable and secure deployments. Collaborate with AI engineers, data engineers, and platform teams to improve the performance, reliability, and cost-efficiency of AI models in production. Drive best practices for observability, including monitoring, alerting, and logging for AI platforms. Contribute to the design and evolution of our AI platform to support new ML frameworks, workflows, and data types. Stay current with new tools and technologies to recommend improvements to architecture and operations. Integrate AI models and large language models (LLMs) into production systems to enable use cases using architectures like retrieval-augmented generation (RAG). 7+ years of professional experience in software engineering and infrastructure engineering. Extensive experience building and maintaining AI/ML infrastructure in production, including model, deployment, and lifecycle management. Expert-level coding skills in TypeScript and Python building robust APIs and backend services. Production-level experience with Databricks MLFlow, including model registration, versioning, asset bundles, and model serving workflows. Expert level understanding of containerization (Docker), and hands on experience with CI/CD pipelines, orchestration tools (e.g., ECS) is a plus. Proven ability to design reliable, secure, and scalable infrastructure for both real-time and batch ML workloads. Strong knowledge of AWS and infrastructure-as-code frameworks, ideally with CDK. Ability to articulate ideas clearly, present findings persuasively, and build rapport with clients and team members. Strong collaboration skills and the ability to partner effectively with cross-functional teams. Nice to Have Familiarity with emerging LLM frameworks for advanced prompt orchestration and programmatic LLM pipelines. Understanding of LLM cost monitoring, latency optimization, and usage analytics in production environments. Knowledge of vector databases / embeddings stores (e.g., OpenSearch) to support semantic search and RAG. Benefits 100% employer-paid benefits for all eligible employees and immediate family members Unlimited paid time off (PTO) 401K Flexible working arrangements - Remote work Company paid Life Insurance, LTD/STD A culture of continuous improvement where you can grow your career and get coaching We are not currently providing visa sponsorship for this position.

Lead architecture and development of a full-stack search platform integrating advanced search and AI models. | Over 10 years backend/platform engineering with expertise in search technologies, Python, TypeScript, semantic retrieval, and distributed systems. | About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you. The Role We're building a search platform that helps scientists find answers across billions of data points from chemical structures and assay results to unstructured lab documents and instrument data. We're looking for a Lead/Principal Platform Engineer to lead that effort. You'll own the full search stack: indexing and scoring, query understanding and rewriting, retrieval pipelines, and the infrastructure underneath it all. You should be able to fluently apply the state-of-the-art in classical search, custom analyzers, index design alongside newer methods for semantic and hybrid retrieval. You'll go well beyond out-of-the-box OpenSearch to build custom ranking logic, relevance tuning, and scoring models that surface the right result from massive, heterogeneous scientific datasets. This is a hands-on technical leadership role. As the technical leader of the Search Platform team, you'll write code, architect systems, mentor engineers, and shape the roadmap for search capabilities and platform evolution. You'll often operate in ambiguous territory translating loosely defined scientific workflows into well-architected search systems where the "right answer" isn't always obvious and requirements evolve as scientists discover new ways to use the platform. You'll collaborate daily with Applied AI Scientists, platform engineers, and product teams to deliver high-performance search services that drive discovery, analysis, and decision-making across the bio-pharma R&D lifecycle. The domain is bio-pharma R&D, and the data types are fascinating molecular structures (SMILES), experimental datasets, knowledge graphs linking compounds to targets and assays. You don't need to know cheminformatics today, but you should be excited to apply deep search expertise to novel and complex data types. If you've spent your career building scalable search systems and want to do it at the intersection of AI and scientific discovery, we'd love to talk. What You will Do Architect a full-stack Search Platform across all layers of indexing and scoring, query understanding, rewriting and federation, and extensible search experiences. Continuously improve search quality through evaluation metrics such as precision@K, recall@K, MRR, and relevance testing with real scientific use cases. Engineer sophisticated hybrid search pipelines that blend sparse (keyword), structured (metadata), and dense (vector) retrieval. You will go beyond out-of-the-box OpenSearch to design custom ranking logic, reciprocal rank fusion, and relevance tuning that surfaces the exact "needle in the haystack" for drug discovery. Lead by example and write code, review designs, and set the standard for engineering quality on the Search Platform team. Mentor engineers and help grow the team's search and distributed systems expertise. Contribute to architectural decisions, technical strategy, and platform-wide improvements to accelerate scientific insight generation. Own and operate the Search Platform infrastructure, ensuring high availability, scalability, performance, and observability across indexing, embedding generation, and query execution. Develop and maintain backend services and APIs in Python and TypeScript that power search capabilities for scientists, data engineers, and AI applications. Ensure security, compliance, and tenant isolation as part of operating search services in enterprise bio-pharma environments. Collaborate with Applied AI Scientists to integrate embeddings, transformer models, and chemical fingerprints into production search workflows. Architect and implement scientific entity resolution and knowledge graph pipelines to transform raw text into interconnected knowledge. You will design systems that extract and link chemical and biological entities (NER/NED) from unstructured documents, enabling the search engine to "understand" relationships between compounds, targets, and assays. 10+ years of backend or platform engineering experience building distributed, production grade systems. Hands-on experience with search technologies such as Elasticsearch/OpenSearch, Lucene, or vector databases not just deployment, but custom configuration, relevance tuning, and performance optimization at scale. Strong understanding of semantic and hybrid retrieval: embeddings, transformer models, vector similarity, ranking logic, relevance tuning, and how to blend them with classical keyword search. Expert-level coding skills in TypeScript and Python building robust APIs and backend services. Proven ability to build and operate search infrastructure on cloud platforms (AWS preferred), including containerization, CI/CD, observability, and capacity planning. Familiarity with scientific or unstructured data processing, such as documents, tables, analytical results, or experimental datasets. Excellent communication and collaboration skills comfortable working alongside scientists, AI researchers, and product teams. Exposure to NLP, LLMs, embedding generation, or retrieval-augmented workflows. Experience with vector databases / embeddings stores (e.g., OpenSearch) to support semantic search and RAG. Strong problem solving skills, while being Comfortable navigating ambiguity translating loosely defined scientific workflows and user needs into well-engineered search systems. Valued Experience Contributions to open-source search projects (Apache Lucene, Solr, OpenSearch, or similar) or active involvement in the search engineering community. Experience with cheminformatics tools and libraries (e.g., RDKit), including molecular fingerprints, similarity metrics, or substructure search. Prior experience implementing chemical search systems, such as SMILES parsing, normalization, or chemical indexing. Experience with entity resolution, knowledge graphs, or NLP pipelines that enrich search corpora. Experience with large-scale data platforms such as Databricks, Lakehouse architectures, or distributed indexing systems. 100% employer-paid benefits for all eligible employees and immediate family members Unlimited paid time off (PTO) 401K Flexible working arrangements - Remote work Company paid Life Insurance, LTD/STD A culture of continuous improvement where you can grow your career and get coaching We are not currently providing visa sponsorship for this position.

Own and maintain documentation pipelines, CI/CD workflows, and infrastructure enabling AI-native content consumption while leading transition to AI-agent based docs and managing editorial quality. | 5+ years in documentation tooling or content engineering with scripting proficiency, experience building LLM-backed workflows, and ability to understand complex codebases. | About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you. The Role TetraScience is the scientific data and AI company. Our documentation is how customers, from bench scientists to platform engineers, learn to build on the platform, and increasingly it is how AI agents consume the platform too. We are looking for a Documentation Engineer to own documentation as a system: the pipelines that build and publish it, the AI-augmented workflows that generate drafts for human review and refinement, the review and publish process, and the infrastructure that makes it reliably consumable by AI agents. This is primarily a documentation systems role, not only a writer who uses tools. The differentiator is building and owning the systems that produce, validate, publish, and AI-enable our documentation. Strong writing and editorial judgment are still required, but the center of gravity is tooling and systems, and a large portion of the day to day is building. You will lead, not just maintain. You will take our existing docs-as-code foundation and AI-assisted documentation workflows and grow them into a docs-as-AI-agents capability that is differentiated for a life-sciences AI platform. You will still own editorial quality and the release-notes cadence, but you will spend most of your time building leverage rather than absorbing work. Own the documentation site and its publishing as software: the docs-as-code repo, the CI/CD publishing pipelines, build performance, and automated link, structure, and quality checks. Build and grow AI-augmented documentation workflows: AI-assisted drafting, summarization, classification, consistency and staleness checks, and a feedback loop that improves generation quality over time, all with human oversight. Build our docs-as-AI-agents position: structure and transform content so AI systems can reliably chunk, index, and reason over it, and stand up and maintain MCP-style interfaces so agents and assistants consume our docs accurately. Generate reference documentation from source (OpenAPI and related specs) and keep docs in lockstep with the platform as code changes. Lower the barrier for internal contributors (PMs, squad leads, engineers) to ship their own docs through the docs-as-code workflow, and reduce repetitive work through automation. Own the release-notes and customer-communications cadence that goes out with every platform release, and run the SME review that keeps it accurate and on time. Own the documentation style guide, hold the review-and-publish gate, and keep the team runbook current so the function is not dependent on any one person. Basics Requirements 5+ years owning documentation tooling, content engineering, or developer documentation for a developer-platform or enterprise B2B product. Engineering ability in a scripting or web stack (for example Python, TypeScript, or JavaScript) and real fluency with docs-as-code: Git, pull-request review, CI/CD, and a static-site or CMS publishing pipeline. Hands-on experience building AI-augmented or LLM-backed workflows: integrating LLM APIs, AI-assisted authoring, and structuring content for AI consumption. Ability to read and reason about a real codebase and API surface well enough to document it accurately and to build tooling against it. Strong editorial judgment: you can take a dense engineering change and make it clear, correct, and customer-safe. Bachelors or Masters degree in a technical field, or equivalent practical experience. Preferred Requirements Experience making documentation consumable by AI agents (llms.txt, content negotiation, RAG pipelines, MCP servers) Experience in BioPharma or scientific software, or in regulated and validated (GxP) environments. Experience generating reference docs from OpenAPI or related specifications with two-way Git sync. Developer-relations or developer-education exposure. US Benefits 100% employer-paid benefits for all eligible employees and immediate family members Unlimited paid time off (PTO) 401K Flexible working arrangements - Remote work Company paid Life Insurance, LTD/STD A culture of continuous improvement where you can grow your career and get coaching We are not currently providing visa sponsorship for this position

Architect and evolve shared platform core services supporting large-scale data and user growth, owning authorization, metadata, governance, and event processing. | 10+ years software engineering experience with proven scaling of distributed cloud-native backend services, expertise in AWS, TypeScript, Python, and infrastructure-as-code frameworks. | Who We Are TetraScience is the Scientific Data and AI Cloud company. We are catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which we bring to life in a growing suite of next gen lab data management solutions, scientific use cases, and AI-enabled outcomes. TetraScience is the category leader in this vital new market, generating more revenue than all other companies in the aggregate. In the last year alone, the world’s dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de facto standard, entering into co-innovation and go-to-market partnerships: In connection with your candidacy, you will be asked to carefully review the Tetra Way letter, authored directly by Patrick Grady, our co-founder and CEO. This letter is designed to assist you in better understanding whether TetraScience is the right fit for you from a values and ethos perspective. It is impossible to overstate the importance of this document and you are encouraged to take it literally and reflect on whether you are aligned with our unique approach to company and team building. If you join us, you will be expected to embody its contents each day. The Role As a Lead Platform Engineer, you will architect and evolve the shared Platform Core services that every other engineering team builds on designed to absorb 100× growth in data volume and users. You'll own the hard cross-cutting primitives authorization, metadata, governance, and high-throughput event processing and act as the technical design authority / SME across product and engineering. This is a highly impactful seat for an engineer who has built authorization and governance systems as products (not just consumed them), understands the trade-offs of large-scale distributed design, and thrives on turning ambitious scalability goals into concrete technical strategy. If you’re excited by the challenge of architecting cloud-native platform to power massive growth and thrive on solving complex scalability problems, we’d love to hear from you. What You will Do Architect and evolve our cloud-native platform and services to support high-throughput, low-latency data processing patterns, customer-facing features, and design platform to meet scalability requirements. Design scalable, distributed systems powering complex capabilities such as authentication & authorization, data lifecycle management, metadata management, operational intelligence, and real-time event processing. Evolve the authorization service toward modern identity standards and customer-configurable, fine-grained access models that scale without a release for every new role including authorization for non-human identities (service-to-service, AI agents, MCP-based tooling). Built systems that capture and enforce structured metadata at ingest and serve it through clean service contracts; understands where platform metadata plumbing ends and the semantic/ontology layer begins, and collaborates well across that boundary. Build governance primitives for a regulated environment — compliance-grade audit trail, dataset-level access controls, and approval / eSignature workflows. Collaborate with engineering and product teams to deliver infrastructure that supports new services, customer-facing applications, and high-volume data processing workloads. Build and maintain infrastructure-as-code (e.g., CloudFormation, AWS CDK) to automate, standardize, and secure deployments to support online upgrades and on-demand infrastructure allocation. Enhance observability and monitoring to ensure reliability, cost efficiency, and rapid incident response. Champion best practices in distributed systems design, scalability, and performance optimization, and share architectural insights through design reviews and technical documentation. 10+ years of hands-on software engineering, with a proven track record of designing, building, and scaling distributed, cloud-native backend services and platforms in production. Demonstrated experience as a technical leader or architect, making key decisions on system design, scalability, performance, and cost optimization. Strong proficiency in API-first design, including REST, GraphQL, and OpenAPI specifications designing APIs that are scalable, secure, versioned, and extensible. Strong proficiency in TypeScript and Python, with a focus on building highly performant backend services. Expertise in AWS cloud services and architecture, including deep experience with core services (e.g., EC2, Lambda, ECS/EKS, IAM, S3) and advanced data and messaging tools such as SQS, Kinesis, Kafka, and EventBridge. Expert knowledge of infrastructure-as-code frameworks such as CloudFormation and CDK, CI/CD pipelines, and strong opinions on production deployment strategy across dozens of platforms. Solid understanding of observability best practices, including monitoring, alerting, and distributed tracing for SLI/SLO/SLA design. Ability to articulate ideas clearly, present findings persuasively, and build rapport with clients and team members. Strong collaboration skills and the ability to partner effectively with cross-functional teams. 100% employer-paid benefits for all eligible employees and immediate family members Unlimited paid time off (PTO) 401K Flexible working arrangements - Remote work Company paid Life Insurance, LTD/STD A culture of continuous improvement where you can grow your career and get coaching

Lead a team to build data models, prototypes, and integration solutions for pre-clinical data and collaborate with stakeholders to deliver data pipelines and Python libraries. | Over 8 years experience in data engineering with Python and SQL proficiency, plus experience with pre-clinical data and dashboarding tools preferred. | About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you. Our core values are designed to guide our behaviors, actions, and decisions such that we operate as one. We are looking to add high-performance team members that authentically and unconditionally embrace our values: Transparency and Context - We trust our people will make the right decisions and overcome any challenges when given data and context. Trust and Collaboration - We believe there can only be trust when there is transparency. We are committed to always communicating openly and honestly. Fearlessness and Resilience - We proactively run toward challenges of all types. We embrace uncertainty and we take calculated risks. Alignment with Customers - We are completely committed to ensuring our customers and partners achieve their missions and treat them with respect and humility. Commitment to Craft - We are passionate missionaries. We sweat the details, as the small things enable the big things. Equality of Opportunity - We seek out the best of the best regardless of gender, ethnicity, race, or age; We seek out those who embody our common values but bring unique and invaluable perspectives, talents, and advantages. What You Will Do You will be leading the Scientific Data Engineering (SDE) Team and helping build Tetra Data and productizable solutions, which is the foundation of the Data Engineering layer. We are looking for a data engineer who is experienced, hands-on, and can also provide mentorship to junior team members. As a Senior Scientific Data Engineer, you should be comfortable leading internal design sessions and architecting solutions. You will work directly with Product Managers and Solution Architects to gather business and data design objectives, resulting in production-based solutions. As a Senior Scientific Data Engineer, you will be a team-focused leader, have excellent data engineering skills, supervise and collaborate on project executions, and have a high commitment to customer success by delivering mission-critical implementations. Our success is defined by collaboration. You will have tremendous support to achieve your objectives, from a variety of teams, both internal and external. Work with Product Managers and Solution Architects to understand business requirements, gather insight into potential positive outcomes, recommend potential outcomes, and build a solution based on consensus. Take ownership of building data models, prototypes, and integration solutions that drive customer success. Use AI agents to build comprehensive data schemas and parsers for pre-clinical data (main data sources: R&D lab instruments, manufacturing, CRO, CDMO, ELN, LIMS) with various data formats: .xlsx, .pdf, .txt, .raw, .fid, many other vendor binaries Extract reusable schema components and parsing functions, and productize them into Python libraries Build high-quality data pipelines with full unit test and integration test coverage to produce high-fidelity data Build data applications, reports, and dashboards using React, Streamlit, Jupyter notebook, etc. Work closely with product managers, project managers, business analysts, data architects, and ML engineers to deliver best-in-class data products Drive value for the customers - verify the solution fulfills their requirements and provides value Quality gatekeeper: design with quality backed by unit tests, integration tests, and utility functions. Lead team-wide process/technology improvements on product quality and developer experience Rally the team to finish Agile Sprint commitments. Actively surfacing team inefficiencies and striving to resolve them. Driven by results. Have the pragmatic urgency to resolve blockers, unclear requirements, and make things happen. Provide mentorship to junior SDEs and show leadership in every front 8+ years of building solutions as a Data Engineer or similar fields 8+ years working in Python and SQL with a focus on data Experience leading projects, managing requirements, and handling timelines Experience managing multiple customer-focused implementation projects across cross-functional teams, building sustainable processes, and managing delivery milestones Experience with data plotting dashboarding tools like React and/or Streamlit is strongly preferred Experience working with pre-clinical data and lab scientists is strongly preferred Excellent communication skills, attention to detail, and the confidence to take control of project delivery. Quickly understand a highly technical product and effectively communicate with product management and engineering. 100% employer paid benefits for all eligible employees and immediate family members. 401K. Unlimited paid time off (PTO). Company paid Life Insurance, LTD/STD. This position isn't eligible for visa sponsorship

As a Lead Platform Engineer, you will architect and evolve the cloud-native Tetra data platform to support high-throughput, low-latency data processing. You will collaborate with engineering and product teams to deliver infrastructure that supports new services and high-volume data processing workloads. | Candidates should have 10+ years of experience in software and infrastructure engineering, with a proven track record in designing and scaling distributed systems. Strong proficiency in TypeScript, Python, and AWS services is required, along with experience in API design and infrastructure-as-code frameworks. | TetraScience is the Scientific Data and AI Cloud company. We are catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which we bring to life in a growing suite of next gen lab data management solutions, scientific use cases, and AI-enabled outcomes. TetraScience is the category leader in this vital new market, generating more revenue than all other companies in the aggregate. In the last year alone, the world’s dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de facto standard, entering into co-innovation and go-to-market partnerships: Latest News and Announcements | TetraScience Newsroom In connection with your candidacy, you will be asked to carefully review the Tetra Way letter, authored directly by Patrick Grady, our co-founder and CEO. This letter is designed to assist you in better understanding whether TetraScience is the right fit for you from a values and ethos perspective. It is impossible to overstate the importance of this document and you are encouraged to take it literally and reflect on whether you are aligned with our unique approach to company and team building. If you join us, you will be expected to embody its contents each day. The Role As a Lead Platform Engineer, you will play a critical role in evolving and scaling our cloud-native Tetra data platform to handle 100× growth in data volume and user demand. You’ll partner with engineering, data, and AI teams to design scalable architectures, proactively anticipate and mitigate scaling challenges, and ensure our platform remains performant, reliable, and cost-efficient as it grows. This is a highly impactful role for an engineer who’s passionate about distributed systems, understands the trade-offs of large-scale design, and thrives on turning ambitious scalability goals into concrete technical strategies. If you’re excited by the challenge of architecting cloud-native infrastructure to power massive growth and thrive on solving complex scalability problems, we’d love to hear from you. What You will Do Architect and evolve our cloud-native platform infrastructure to support high-throughput, low-latency data processing patterns, customer-facing features, and design platform to meet scalability requirements. Design scalable, distributed systems powering complex capabilities such as authentication & authorization, data lifecycle management, search infrastructure, operational intelligence, and real-time event processing. Proactively analyze platform performance and scalability; identify potential constraints and define strategies that enable both continuous and step-function growth. Collaborate with engineering and product teams to deliver infrastructure that supports new services, customer-facing applications, and high-volume data processing workloads. Build and maintain infrastructure-as-code (e.g., CloudFormation, AWS CDK) to automate, standardize, and secure deployments to support online upgrades and on-demand infrastructure allocation. Enhance observability and monitoring to ensure reliability, cost efficiency, and rapid incident response. Champion best practices in distributed systems design, scalability, and performance optimization, and share architectural insights through design reviews and technical documentation. 10+ years of hands-on experience in software and infrastructure engineering, with a proven track record of designing, building, and scaling distributed, cloud-native systems in production environments. Demonstrated experience as a technical leader or architect, making key decisions on system design, scalability, performance, and cost optimization. Strong proficiency in API-first design, including REST, GraphQL, and OpenAPI specifications designing APIs that are scalable, secure, versioned, and extensible. Strong proficiency in TypeScript and Python, with a focus on building highly performant backend services. Expertise in AWS cloud services and architecture, including deep experience with core services (e.g., EC2, Lambda, ECS/EKS, IAM, S3) and advanced data and messaging tools such as SQS, Kinesis, Kafka, and EventBridge. Expert knowledge of infrastructure-as-code frameworks such as CloudFormation and CDK, CI/CD pipelines, and strong opinions on production deployment strategy across dozens of platforms. Solid understanding of observability best practices, including monitoring, alerting, and distributed tracing for SLI/SLO/SLA design. Ability to articulate ideas clearly, present findings persuasively, and build rapport with clients and team members. Strong collaboration skills and the ability to partner effectively with cross-functional teams. 100% employer-paid benefits for all eligible employees and immediate family members Unlimited paid time off (PTO) 401K Flexible working arrangements - Remote work Company paid Life Insurance, LTD/STD A culture of continuous improvement where you can grow your career and get coaching We are not currently providing visa sponsorship for this position.

As a Lead Platform Engineer, you will architect and evolve the cloud-native Tetra data platform to support high-throughput data processing and scalability. You will collaborate with engineering and product teams to deliver infrastructure that meets the demands of new services and high-volume workloads. | Candidates should have 10+ years of experience in software and infrastructure engineering with a strong background in designing and scaling distributed systems. Proficiency in TypeScript, Python, and AWS services is essential, along with experience in API design and infrastructure-as-code. | TetraScience is the Scientific Data and AI Cloud company. We are catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which we bring to life in a growing suite of next gen lab data management solutions, scientific use cases, and AI-enabled outcomes. TetraScience is the category leader in this vital new market, generating more revenue than all other companies in the aggregate. In the last year alone, the world’s dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de facto standard, entering into co-innovation and go-to-market partnerships: Latest News and Announcements | TetraScience Newsroom In connection with your candidacy, you will be asked to carefully review the Tetra Way letter, authored directly by Patrick Grady, our co-founder and CEO. This letter is designed to assist you in better understanding whether TetraScience is the right fit for you from a values and ethos perspective. It is impossible to overstate the importance of this document and you are encouraged to take it literally and reflect on whether you are aligned with our unique approach to company and team building. If you join us, you will be expected to embody its contents each day. The Role As a Lead Platform Engineer, you will play a critical role in evolving and scaling our cloud-native Tetra data platform to handle 100× growth in data volume and user demand. You’ll partner with engineering, data, and AI teams to design scalable architectures, proactively anticipate and mitigate scaling challenges, and ensure our platform remains performant, reliable, and cost-efficient as it grows. This is a highly impactful role for an engineer who’s passionate about distributed systems, understands the trade-offs of large-scale design, and thrives on turning ambitious scalability goals into concrete technical strategies. If you’re excited by the challenge of architecting cloud-native infrastructure to power massive growth and thrive on solving complex scalability problems, we’d love to hear from you. What You will Do Architect and evolve our cloud-native platform infrastructure to support high-throughput, low-latency data processing patterns, customer-facing features, and design platform to meet scalability requirements. Design scalable, distributed systems powering complex capabilities such as authentication & authorization, data lifecycle management, search infrastructure, operational intelligence, and real-time event processing. Proactively analyze platform performance and scalability; identify potential constraints and define strategies that enable both continuous and step-function growth. Collaborate with engineering and product teams to deliver infrastructure that supports new services, customer-facing applications, and high-volume data processing workloads. Build and maintain infrastructure-as-code (e.g., CloudFormation, AWS CDK) to automate, standardize, and secure deployments to support online upgrades and on-demand infrastructure allocation. Enhance observability and monitoring to ensure reliability, cost efficiency, and rapid incident response. Champion best practices in distributed systems design, scalability, and performance optimization, and share architectural insights through design reviews and technical documentation. 10+ years of hands-on experience in software and infrastructure engineering, with a proven track record of designing, building, and scaling distributed, cloud-native systems in production environments. Demonstrated experience as a technical leader or architect, making key decisions on system design, scalability, performance, and cost optimization. Strong proficiency in API-first design, including REST, GraphQL, and OpenAPI specifications designing APIs that are scalable, secure, versioned, and extensible. Strong proficiency in TypeScript and Python, with a focus on building highly performant backend services. Expertise in AWS cloud services and architecture, including deep experience with core services (e.g., EC2, Lambda, ECS/EKS, IAM, S3) and advanced data and messaging tools such as SQS, Kinesis, Kafka, and EventBridge. Expert knowledge of infrastructure-as-code frameworks such as CloudFormation and CDK, CI/CD pipelines, and strong opinions on production deployment strategy across dozens of platforms. Solid understanding of observability best practices, including monitoring, alerting, and distributed tracing for SLI/SLO/SLA design. Ability to articulate ideas clearly, present findings persuasively, and build rapport with clients and team members. Strong collaboration skills and the ability to partner effectively with cross-functional teams. 100% employer-paid benefits for all eligible employees and immediate family members Unlimited paid time off (PTO) 401K Flexible working arrangements - Remote work Company paid Life Insurance, LTD/STD A culture of continuous improvement where you can grow your career and get coaching We are not currently providing visa sponsorship for this position.

Lead and grow the Americas sales team to drive revenue growth in life sciences R&D software by managing complex enterprise deals and expanding customer base. | 10+ years selling life sciences R&D software with 3-5 years sales management, experience with large pharma accounts, complex enterprise deals, and startup environments. | Who We Are TetraScience is the Scientific Data and AI company. We are catalyzing the Scientific AI revolution by industrializing the production of AI-native scientific data and AI-enabled use cases across the value chain. TetraScience is the category leader in this vital new market. In the last year alone, the world's dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de facto standard, entering into co-innovation and go-to-market partnerships: Latest News and Announcements TetraScience Newsroom In connection with your candidacy, you will be asked to carefully review the Tetra Way letter, authored directly by Patrick Grady, our CEO. This letter is designed to assist you in better understanding whether TetraScience's values and ethos are the right fit for you. It is impossible to overstate the importance of this document and you are encouraged to take it literally and reflect on whether you are aligned with our unique approach to company and team building. If you join us, you will be expected to embody its contents daily. Who You Are TetraScience is hiring an elite field operations leader to oversee the Americas. You will report directly to the CEO, work closely with the balance of the leadership team, and you will own the number for the Americas business. Full stop. As we rapidly evolve our platform and open up new value creation paths with new SKUs and new personas, we require an uncompromising and results-driven sales leader to help us expand within our customer base and acquire new leading pharmaceutical customers. You will need to be a high clock speed and forward-thinking individual with a passion for selling complex and multi-persona solutions inside of Life Sciences. As a player you will fundamentally embody the principles of extreme ownership and have a demonstrated history of selling complex, enterprise class deals - from initial lands through to ELAs. As a coach you will have a demonstrated history of building and leading high-performing sales teams. Beyond your direct reports you will have demonstrable experience in cross-functional and cross-enterprise collaboration. You will lead from the front, calling plays, setting the tempo, and ensuring your team delivers against their numbers. You are not a passive role player. You will have demonstrable experience in managing the day-to-day activities of your teams and building accurate and reliable forecasts with proof of consistently exceeding annual and quarterly revenue targets. Again, you are a player-coach and not a spectator. You will travel to customers, pitch the vision, and close your own deals as well as directing and coaching a rapidly expanding team of AEs. For the avoidance of doubt, we remain in the category creation and evangelism phase and thus you are not coming in to be an order-taker or career coach. It will require extreme self-discipline and determination as we forge a category that will fundamentally and forever change the life sciences industry. What You Will Do • Develop and execute a comprehensive sales strategy to drive revenue growth and meet annual sales targets. • Identify and pursue new business opportunities, expanding our customer base across the biopharma value chain. • Stay up-to-date on industry trends and emerging technologies, positioning TetraScience as a thought leader in the market. • Work closely with marketing and product teams to develop and implement go-to-market strategies and campaigns. • Lead compelling presentations of TetraScience to a range of audiences from R&D IT, Informatics, Scientists and Data Scientists to Directors, VPs, CDOs and Digital Transformation Executives. • Leverage and coordinate cross-functional teams, when necessary (Legal, Engineering, Marketing, Product), to efficiently navigate complex sales cycles. • Aligning to the sales strategy, you will define and implement plans for the assigned accounts to achieve sales objectives. • Maintain ongoing relationships with existing customers, ensuring high levels of customer satisfaction and retention. • Manage sales forecasting and reporting and regularly update senior leadership on progress toward targets. • Build and manage a high-performance sales team, setting clear targets and objectives to ensure individual and team success. • You will coach your team to develop in their careers and inspire your team to do the best work of their life but will be completely comfortable inspecting and directing alongside coaching. • Employ analytical skills and the ability to generate insights from data. Requirements What You Have Done • 10+ years selling to the life sciences R&D software and data market • Of that 10 years; 3-5 years in a sales management role (Regional or District Manager perhaps) • Significantly curious about the scientific data problems of the pharma industry - you will have interfaced with and influenced VPs and above, in both scientific and IT functions • Some experience in leading a team of account executives but also still hands on with deals every day • Worked in startup environments • Sold to and led successful teams in the Top 100 Pharma cohort (not biotech) • Sold large and complex enterprise deals - $ millions to tens of millions in ARR per deal • Created and scaled the highest performing teams in your orgs meeting quota every quarter without fail • Clear evidence of pushing the broader team to direct product marketing efforts to grow your business • Clear evidence of having expanded accounts through protracted, gritty, forward deployed engagement of a broader set of account teams • Evidenced strong leadership skills while navigating difficult periods with your team • Operated effectively in a fast-paced, team environment - completely comfortable working in a "win as a team" environment Benefits • 100% employer-paid benefits for all eligible employees and immediate family members. • Unlimited paid time off (PTO). • 401K. • Flexible working arrangements - Remote work + office as needed. • Company paid Life Insurance, LTD/STD.

Lead UX design for AI-driven scientific workflows, collaborate cross-functionally to define UX roadmaps, conduct user research with pharmaceutical clients, and evolve design systems for enterprise scientific users. | 10+ years UX design experience with 3+ years leading AI/ML platforms in life sciences, portfolio of scientific interfaces, collaboration with AI teams, familiarity with regulated environments, and proficiency in rapid prototyping tools. | Who We Are TetraScience is the Scientific Data and AI Cloud company. We are catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which we bring to life in a growing suite of next gen lab data management solutions, scientific use cases, and AI-enabled outcomes. TetraScience is the category leader in this vital new market. In the last year alone, the world’s dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de facto standard, entering into co-innovation and go-to-market partnerships: Latest News and Announcements | TetraScience Newsroom In connection with your candidacy, you will be asked to carefully review the Tetra Way letter, authored directly by Patrick Grady, our co-founder and CEO. This letter is designed to assist you in better understanding whether TetraScience is the right fit for you from a values and ethos perspective. It is impossible to overstate the importance of this document and you are encouraged to take it literally and reflect on whether you are aligned with our unique approach to company and team building. If you join us, you will be expected to embody its contents each day. What You Will Do Design AI-Powered Scientific Workflows (60-80% hands-on): Lead end-to-end UX design for AI-driven features, including wireframes, prototypes, and high-fidelity interfaces that integrate scientific data inputs (e.g., assays, instruments, ELN/LIMS) with AI model outputs. Collaborate with platofrm and science teams to translate algorithmic decision-making processes into intuitive user interactions. Strategic Vision & Cross-Functional Leadership: Partner with product managers and scientific stakeholders to define UX roadmaps that align with platform adoption goals. Advocate for user-centric design in AI product development, balancing technical feasibility with scientific user needs. Customer-Facing Research & Validation: Conduct lightweight user research directly with pharmaceutical clients to identify pain points in lab workflows. Rapidly prototype solutions and iterate based on stakeholder feedback, prioritizing high-impact improvements. Evolving Design Systems: Enhance existing design patterns and components to ensure consistency across AI-driven features, focusing on scalability for enterprise scientific users. Requirements • 10+ years of UX design experience, with 3+ years leading AI/ML-powered enterprise platforms in life sciences, healthcare, or regulated environments. • Portfolio demonstrating end-to-end ownership of scientific interfaces including complex data visualization, AI interface design, and workflow optimization for non-technical users • Proven ability to influence product strategy by translating scientific workflows into AI interaction patterns (e.g., multi-model comparisons, iterative retraining interfaces). • Experience collaborating with scientists or AI teams to design interfaces that expose model inputs/outputs, uncertainty metrics, and feedback mechanisms. • Familiarity with life sciences workflows (e.g., assay development, computational biology) and regulated environments (GxP, FDA). • Proficiency in Figma, Miro, or similar tools for rapid prototyping. • Strong Communicator. You communicate clearly and persuasively in multiple mediums with product managers, engineers, stakeholders, and customers. Preferred Qualifications • Advanced degree in HCI, Cognitive Science, or related field. • Published research/presentations on AI-human collaboration in scientific contexts. Benefits Benefits US • 100% employer-paid benefits for all eligible employees and immediate family members • Unlimited paid time off (PTO) • 401K • Flexible working arrangements - Remote work • Company paid Life Insurance, LTD/STD • A culture of continuous improvement where you can grow your career and get coaching We are not currently providing visa sponsorship for this position