Senior Engineer, Bioinformatics

Description

The company is a public benefit corporation headquartered in San Francisco that builds AI systems meant to be reliable, interpretable, and steerable, and safe and useful for people and society at large. The team is a fast-growing group of researchers, engineers, policy experts, and business leaders.

This senior software engineering role sits on the Life Sciences team, which uses frontier models alongside computational and lab research to speed up biology. You will build biology software for the company's own scientists and for the wider research community, and you will be a main point of contact for computational biologists outside the company.

The team plans to publish its tools, pipelines, datasets, and benchmarks in genomics and structural biology. Each release should install easily, run on a user's own data, and give results checked against reference data and established methods, with documentation, versioning, and ongoing maintenance.

You will own that standard, writing much of the code yourself, deciding when work is ready, and staying with it after users adopt it. You will also take part in the biology software community through public repositories, issues, conferences, and workshops.

The company relies heavily on Claude and other AI coding agents. Agent-written code faces the same review, testing, and performance checks as hand-written code.

The role can be mostly individual contributor work or can include leading a small group of engineers and scientists. You may focus on genomics, structural biology, or both, and other areas of computational biology are welcome. The scope is expected to widen over time.

The most important evidence is a record of biology software that others have adopted and depended on.

Responsibilities

• Build and maintain genomics and structural biology software, including libraries, command-line tools, pipelines, datasets, and benchmarks, for researchers and AI agents both inside and outside the company.
• Take research code to public release, covering testing, validation against reference data and standard tools, benchmarking, documentation, and packaging. Decide when a release is ready to ship.
• Keep released software working by triaging issues, reviewing outside contributions, and managing breaking changes.
• Represent the team at conferences, workshops, and tutorials, and work directly with researchers and maintainers. Turn what you learn about their needs into team priorities.
• Work with the team's computational and experimental scientists to turn research code into tested, reusable software.
• Set technical direction for your projects through design review, code review, and mentoring. Depending on your interests and the team's needs, lead a small team.
• Make Claude and other coding agents your everyday way of working, apply the same bar to agent code as to your own, and define the team's practices for reviewing and validating it.

Requirements

• Have built, released, and maintained biology software that researchers outside your group use, with evidence such as public repositories, package downloads, citations, or use in other groups' pipelines.
• Have deep working knowledge of genomics or structural biology, including data types, file formats, standard tools, and common failure modes in at least one field.
• Write strong Python and work comfortably with large datasets on Linux and in cloud or cluster environments.
• Apply rigorous testing and release engineering: unit and integration tests, continuous integration, validation against reference data, packaging, and versioning.
• Use AI coding tools as a core part of how you build software, and show how you check the correctness and performance of code you did not write yourself.
• Have led a technical project with several contributors, setting direction and reviewing their work while still writing code.
• Explain technical work clearly to biologists and engineers, in writing through documentation and tutorials and in person through talks and workshops.
• Hold a bachelor's degree or an equivalent mix of education, training, and experience, in a field relevant to the role as shown by coursework, training, or work history. Years of experience match the internal level for the position.
• Preferred: depth in both genomics and structural biology.
• Preferred: a record as the creator or core maintainer of a widely used open-source tool in computational biology.
• Preferred: experience managing or formally leading engineers or scientists.
• Preferred: a graduate degree in computational biology, bioinformatics, computer science, or a related field, or equivalent experience.
• Preferred: proficiency in a systems language such as Rust, C++, or C, and experience with performance work on large biological datasets.
• Preferred: experience building software in other areas of computational biology, such as phylogenetics, proteomics, cheminformatics, or high-throughput screen analysis.
• Preferred: experience shipping software built largely with AI coding agents, building agentic systems on large language models, or training machine learning models on biological sequence or structure data.

Conditions

The annual base salary range is $300,000 to $320,000 USD.

Staff are expected in an office at least 25% of the time under the location-based hybrid policy, and some roles require more office time.

Visa sponsorship is available, but not for every role or candidate. If an offer is made, the company will make every reasonable effort to obtain a visa and retains an immigration lawyer to help.

Candidates are encouraged to apply even without meeting every listed qualification, since the company wants a range of perspectives on the team.

Benefits

• Pay and benefits are competitive.
• Optional matching for equity donations.
• Vacation and parental leave are generous.
• Flexible working hours.
• An office space designed for collaboration with colleagues.