Senior Engineer, BioinformaticsSenior Engineer, Bioinformatics

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role

As a Senior Software Engineer on the Life Sciences team, you'll build biology software that our own scientists and the wider research community can depend on, and you'll be one of the main people representing that work to computational biologists outside Anthropic.

The Life Sciences team works to accelerate progress in biology with AI, combining frontier models with hands-on computational and experimental research. We want the tools, pipelines, datasets, and benchmarks we build in genomics and structural biology to be useful beyond our own projects, so we plan to release them to the community. Computational biology has a long tradition of open, shared software, and we want to contribute to it well. Every release should be something a researcher can install, run on their own data, and trust: correct on real inputs, validated against reference data and established methods, documented, versioned, and maintained after launch.

You'll own that standard. You'll write a large share of the code yourself, decide when something is ready to ship, and stay with it once people start using it. You'll also be an active member of the biology software community: maintaining public repositories, answering issues, speaking at conferences and workshops, and bringing what you hear from researchers back into what we build next.

We use Claude and AI coding agents heavily to build software, and we expect you to do the same across design, implementation, testing, and review. Code written by an agent is held to the same standard as code written by hand: you should understand it, test it, and measure its performance before it ships. We're looking for someone with deep software engineering experience who already works this way.

The shape of the role is flexible. You might spend most of your time as an individual contributor, or you might lead a small group of engineers and scientists while continuing to contribute directly. Your focus can be genomics, structural biology, or both. Experience in other areas of computational biology is welcome, and we expect the work to range more widely over time. 

What matters most is a record of biology software that other people have adopted and relied on.

This is a chance to shape how AI is put to work in biological research, on problems that matter for human health and scientific understanding. If building software that scientists trust is the work you want to do, we want to hear from you.

Key responsibilities

• Design, build, and maintain biology software in genomics and structural biology (libraries, command-line tools, pipelines, datasets, and benchmarks) for use by researchers and AI agents, inside Anthropic and externally

• Own the path from research code to public release, including testing, validation against reference data and established tools, benchmarking, documentation, and packaging, and make the call on when something is ready to ship

• Maintain what we release: triage issues, review outside contributions, and manage breaking changes

• Represent the team in the biology community through conferences, workshops, tutorials, and direct work with researchers and maintainers, and turn what you learn about their needs into priorities for the team

• Partner with the team's computational and experimental scientists to turn research code into well-tested, reusable software

• Lead the technical direction of the projects you own through design review, code review, and mentoring, and, depending on your interests and the team's needs, lead a small team

• Build with Claude and AI coding agents as your default way of working, hold agent-written code to the same standard as your own, and set the team's practices for reviewing and validating it

Minimum qualifications

• Have built, released, and maintained biology software that researchers outside your own group use, with evidence of adoption you can point to (for example public repositories, package downloads, citations, or use in other groups' pipelines)

• Have deep working expertise in genomics or structural biology, including the data types, file formats, standard tools, and common failure modes of at least one of these fields

• Are proficient in Python and comfortable working with large datasets in Linux and cloud or cluster computing environments

• Practice rigorous testing and release engineering: unit and integration tests, continuous integration, validation against reference data, packaging, and versioning

• Use AI coding tools as a central part of how you build software, and can show how you verify the correctness and performance of code you did not write by hand

• Have led a technical project with multiple contributors, setting direction and reviewing others' work while continuing to write code yourself

• Can explain technical work clearly to both biologists and engineers, in writing (documentation, tutorials) and in person (talks, workshops)

Preferred qualifications

• Depth in both genomics and structural biology

• A record as the creator or a core maintainer of a widely used open-source tool in computational biology

• Experience managing or formally leading a team of engineers or scientists

• A graduate degree in computational biology, bioinformatics, computer science, or a related field, or equivalent experience

• Proficiency in a systems language such as Rust, C++, or C, and experience with performance work on large biological datasets

• Experience building software in other areas of computational biology, such as phylogenetics, proteomics, cheminformatics, or high-throughput screen analysis

• 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

The annual compensation range for this role is listed below. 

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:$300,000—$320,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.