# Manager, Applied AI Engineering, Life Sciences

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA, New York, NY
**Role:** Engineering Management
**Salary:** $320k – $405k/yr
**Experience:** 7+ years
**Skills:** Python, Machine Learning, LLMs, Agent Systems, Bioinformatics, Computational Biology, Data Infrastructure, Mcp Integrations, Scientific Computing, Production Code
**Posted:** 2026-06-24

> Lead a team of Applied AI Engineers deploying Claude for Life Sciences at top pharma and biotech organizations. Hands-on manager responsible for technical success of strategic deployments, building agent-ready scientific infrastructure, and translating field learnings into product improvements.

## Job Description

## 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.
- Own technical 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.
- Are 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.

## Nice-to-Haves
- 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.

## Compensation & Benefits
- Annual Salary: $320,000–$405,000 USD
- 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 available.

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