Manager, Applied AI Engineering, Beneficial Deployments (Life Sciences)

Details

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems.

About the role

Biology is the area where scientific progress has perhaps the greatest potential to directly and unambiguously improve human life—and we believe powerful AI could meaningfully accelerate the rate of biological discovery.

With Claude for Life Sciences, Anthropic is building tools that accelerate the work of scientists and drug developers across the full lifecycle, from early discovery through clinical translation and regulatory review.

As the Applied AI Engineering Manager for Life Sciences, you will lead the team of engineers who turn this ambition into deployed reality inside the world's leading scientific organizations. Applied AI Engineers are the technical front line: they sit with customers, understand their scientific and regulatory workflows in depth, and build prototypes, integrations, and agents that let Claude do meaningful work in the lab and the clinic.

This role emphasizes that “it’s more than wiring up a chatbot.” The hard part is the infrastructure beneath agents: messy databases, idiosyncratic file formats, scattered APIs, and metadata conventions where a single wrong or missing record can change a scientific conclusion. Your team builds deterministic tools, connectors, and evaluations that make biological data reliably accessible to agents—and holds the work to a research-grade bar where an answer has to be correct, reproducible, and auditable.

Because this work sits in a sensitive, dual-use domain, you will also help set the standard for how Anthropic deploys responsibly.

In this role, you will

• Build and lead the team: hire, coach, and develop a team of Applied AI Engineers dedicated to strategic life sciences partners, setting a high technical bar.
• Own technical success with partners: be accountable for the technical outcomes of strategic pharma and biotech deployments, from first scoping conversation through production.
• Stay hands-on: review and contribute to prototypes, MCP integrations, agentic workflows, and Claude Code for Bio solutions; help the team get unblocked on the hardest technical problems.
• Build agent-ready scientific infrastructure: guide the team in creating deterministic tools, connectors/harnesses, and evaluations that make messy biological data and workflows reliably accessible to Claude (in partnership with scientists and research institutions).
• Translate the field into the roadmap: partner cross-functionally to turn learnings from deployments into improvements in Anthropic’s life sciences products and models.
• Set the standard for responsible deployment: work alongside safety teams to enable beneficial scientific work while guarding against misuse in a dual-use domain.
• Build for the frontier: use deep knowledge of frontier model intelligence coupled to work in R&D and research to progress toward solutions to meaningful problems in life sciences.

You may be a good fit if you

• Have led or technically mentored software/ML engineers, ideally in a forward-deployed, solutions, or customer-facing engineering setting.
• Have a background in pharma, biotech, computational biology, bioinformatics, or clinical/regulatory affairs.
• Have a strong hands-on engineering background and are comfortable reading and writing production code, not just managing those who do.
• Have delivered technical work directly with external customers or partners, and can communicate credibly with both technical experts and executives.
• Have built on top of large language models or agents.
• Are energized by an unfamiliar technical domain and have a track record of going deep fast.
• Hold a high bar for reliability and reproducibility; understand why a plausible-looking answer that is subtly wrong can be worse than no answer in scientific work.
• Have built tooling, data infrastructure, evals, or agent harnesses that turn messy real-world data into something usable and trustworthy—especially in scientific or research settings.
• Care deeply about the safe and beneficial deployment of AI, especially in sensitive domains.

Strong candidates may also have

• Experience deploying LLM or agent systems in regulated or enterprise environments.
• Experience building MCP servers, developer tooling, or scientific computing pipelines.
• Experience scaling a customer-facing technical team through a period of rapid growth.

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: Will correlate with internal job level requirements.
• Location-based hybrid policy: Currently expected to be in one of the offices at least 25% of the time (some roles may require more time).
• Visa sponsorship: Anthropic sponsors visas, and if an offer is made, they will make every reasonable effort to get you a visa (they retain an immigration lawyer to help).

Come work with us

Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office space.