Senior Engineer, Bioinformatics
Anthropic · San Francisco, CA
About this role
**Senior Engineer, Bioinformatics — Anthropic (Life Sciences Team)** ## About the role As a **Senior Software Engineer** on the **Life Sciences** team, you’ll build biology software that scientists and the broader research community can rely on. You’ll also represent this work to computational biologists outside Anthropic. The team accelerates progress in biology with AI—combining frontier models with hands-on computational and experimental research. You’ll help create tools, pipelines, datasets, and benchmarks in **genomics** and **structural biology** that are designed to be released to the community: installable, runnable on researchers’ own data, correct on real inputs, validated against reference data and established methods, well-documented, versioned, and maintained after launch. You’ll own the standard end-to-end: writing a large share of the code, deciding when something is ready to ship, and staying with it once others start using it. You’ll also actively engage with the biology software community by maintaining public repositories, answering issues, speaking at conferences/workshops, and feeding what you learn back into future work. We use **Claude** and **AI coding agents** heavily. Agent-written code is held to the same standard as code written by hand—you must understand it, test it, and measure performance before it ships. ## Key responsibilities - **Design, build, and maintain** biology software in genomics and structural biology (libraries, CLI tools, pipelines, datasets, benchmarks) for internal and external researchers/AI agents. - **Own the path from research code to public release**, including testing, validation against reference data and established tools, benchmarking, documentation, and packaging—plus the judgment on when to ship. - **Maintain what you release**: triage issues, review outside contributions, and manage breaking changes. - **Represent the team in the biology community** via conferences, workshops, tutorials, and direct collaboration with researchers/maintainers; translate feedback into team priorities. - **Partner with computational and experimental scientists** to turn research code into well-tested, reusable software. - **Lead technical direction** through design/code review and mentoring; depending on needs, lead a small group. - **Build with Claude/AI agents as a default workflow**, and set team practices for reviewing and validating agent-written code. ## Minimum qualifications - Evidence of having **built, released, and maintained biology software** used by researchers outside your group (e.g., public repos, downloads, citations, or use in others’ pipelines). - Deep working expertise in **genomics or structural biology**, including data types, file formats, standard tools, and common failure modes. - Proficient in **Python**, comfortable with **large datasets** in **Linux** and **cloud/cluster** environments. - Strong **testing and release engineering** practices (unit/integration tests, CI, validation against reference data, packaging, versioning). - Ability to use **AI coding tools centrally** and demonstrate how you verify correctness/performance of code you didn’t write by hand. - Experience leading a technical project with multiple contributors (direction + reviewing others’ work while continuing to code). - Can explain technical work clearly to both **biologists and engineers** (documentation/tutorials and in-person talks/workshops). ## Preferred qualifications - Depth in **both
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