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

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, helping compress decades of progress into years. With Claude for Life Sciences, we're building tools that accelerate the work of scientists and drug developers across the full lifecycle, from early discovery through clinical translation and regulatory review.

Responsibilities

• 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 and helping each engineer grow.
• Owntechnical success with partners: be accountable for the technical outcomes of our 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 the 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 what you learn from deployments into improvements in Anthropic's life sciences products and models.
• Set the standard for responsible deployment: work alongside our 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 your work in R&D and research to rapidly progress toward solutions to meaningful problems in life sciences.

Requirements

• 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.
• Be energized by an unfamiliar technical domain and have a track record of going deep fast.
• Hold a high bar for reliability and reproducibility, and understand why a plausible-looking answer that's 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 welcome if in a scientific or research setting.
• Care deeply about the safe and beneficial deployment of AI, especially in sensitive domains.

Qualifications

• Years of experience required will correlate with the internal job level requirements for the position.
• 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.

Skills

• 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.

Benefits

• Competitive compensation and benefits.
• Optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours.
• A lovely office space in which to collaborate with colleagues.

Pay

The annual compensation range for this role is listed below.

• Annual Salary: $320,000 - $405,000 USD

Schedule

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.

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

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.