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

at Anthropic

📍 New York City, United States
📍 San Francisco, United States

USD 320,000-405,000 per year

MIDDLE

✅ Hybrid

✅ Visa Sponsorship

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 3 API Claude Code LLM @ 3 Machine Learning @ 3 Mentoring @ 3 Technical Leadership

Details

Anthropic is building Claude for Life Sciences to 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 engineers who build and deploy prototypes, integrations, agents, deterministic tools, connectors, and evaluations for strategic pharma and biotech partners. The role combines hands-on technical leadership, customer-facing engineering, team development, product and research collaboration, and responsible AI deployment in a sensitive dual-use domain.

The team works with messy biological databases, idiosyncratic file formats, scattered APIs, and metadata conventions. Its systems must make biological data reliably accessible to agents and meet a research-grade standard of correctness, reproducibility, and auditability.

Responsibilities

Hire, coach, and develop a team of Applied AI Engineers supporting strategic life sciences partners.
Own the technical outcomes of strategic pharma and biotech deployments from initial scoping through production.
Review and contribute to prototypes, MCP integrations, agentic workflows, and Claude Code for Bio solutions.
Help resolve complex technical problems and remain hands-on with production engineering.
Guide the development of deterministic tools, connectors and harnesses, and evaluations that make biological data and workflows reliably accessible to Claude.
Partner with scientists and research institutions to build agent-ready scientific infrastructure.
Translate deployment insights into improvements for Anthropic’s life sciences products and models.
Work with safety teams to enable beneficial scientific work while guarding against misuse.
Apply knowledge of frontier model intelligence to R&D and research in life sciences.

Requirements

Experience leading or technically mentoring software or machine learning engineers, ideally in a forward-deployed, solutions, or customer-facing engineering environment.
Background in pharma, biotech, computational biology, bioinformatics, or clinical and regulatory affairs.
Strong hands-on engineering background with the ability to read and write production code.
Experience delivering technical work directly with external customers or partners and communicating with technical experts and executives.
Experience building on large language models or agents.
Ability to learn unfamiliar technical domains quickly.
High standards for reliability and reproducibility, with an understanding of the risks of subtly incorrect scientific outputs.
Experience building tooling, data infrastructure, evaluations, or agent harnesses that make messy real-world data usable and trustworthy, particularly in scientific or research settings.
Commitment to the safe and beneficial deployment of AI in sensitive domains.

Additional Qualifications

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 during rapid growth.

Education and 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, demonstrated through coursework, training, or professional experience.
Minimum years of experience: Requirements correlate with the internal job level.
Hybrid policy: Staff are expected to work from one of Anthropic’s offices at least 25% of the time, though some roles may require more office time.
Anthropic sponsors visas and makes reasonable efforts to obtain a visa for candidates when an offer is made, although sponsorship is not guaranteed for every role or candidate.