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Foresite Labs

Software Engineer, AI Agents

san francisco, CA

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About this opportunity

Foresite Labs lists this Software Engineer, AI Agents opportunity in san francisco, California. Review the employer’s description below for duties, qualifications and application requirements.

Job description

Foresite Labs is a translational R&D team that derives insights from precision measurement and population-scale biology and genetics to address unmet clinical needs. We use human genetics to systematically dissect and understand human disease biology and develop and critically evaluate therapeutic hypotheses. We engage in translational research, transforming basic insights into therapeutic opportunities. Our work supports drug discovery and company formation, and provides the core around which new ideas are realized and incubated. We offer competitive salaries, excellent benefits, a flexible work environment, and the opportunity to learn from top thinkers in various disciplines. Foresite Labs is headquartered in San Francisco.

The Role

We're hiring a software engineer to help create the data pipelines, machine learning infrastructure, and agentic systems that power our science. On the agentic side, that means writing the code that runs the loop an AI agent operates inside, not one-off prompts — designing how agents plan, call tools, orchestrate sub-agents, keep memory, check their own work, and decide when they're done, then shipping them into production to do real work across our genetics and drug-discovery pipeline. This is \"loop engineering\": the model writes the prompts; you build and harden the machinery around it.

It's a full-stack, high-ownership role on a small senior team. You'll take systems from a blank repo to production and work shoulder-to-shoulder with ML engineers, computational biologists, and scientists.

What You’ll Do

Build agent loops end-to-end — tool/function calling, planning, sub-agent orchestration, memory, and control flow that runs reliably and unsupervised

Build the eval and observability harness — the tests, metrics, tracing, and guardrails that make agentic systems trustworthy in production

Turn scientific and operational workflows into agents that take real action across our platform

Ship full-stack features: React/Tailwind front ends and backend services that put these agents in front of scientists

Design and launch production-grade systems, services, data pipelines, and machine learning infrastructure from scratch

Use frontier AI-native development tools (e.g. Claude Code) to move fast

Uphold engineering standards through code review, testing, and peer mentorship

What You’ll Bring

5+ years of professional software engineering, with greenfield systems you've shipped to production

Hands-on experience building LLM/agent systems in production — agent loops, tool calling, RAG, and evals (frameworks like LangChain, Pydantic AI, or equivalent)

Fluency in TypeScript plus a modern backend language (Python, Go, or Java)

Working knowledge of AWS/GCP/Azure core services and infrastructure-as-code (Terraform, CDK, or Pulumi)

Comfort in Unix, Docker, and CI/CD pipelines

Early-stage execution mindset and strong ownership

Clear communication across technical and non-technical audiences

Nice to Have

Experience with LLM eval / observability tooling (e.g. LangSmith) and prompt/loop iteration at scale

Multi-agent orchestration in production

Interest in biology, genetics, or human health — no life-sciences background required

Why Foresite Labs

Build frontier agentic products that measurably accelerate real drug discovery

Greenfield work, end-to-end ownership, and architecture decisions without bureaucracy

A small, senior team working directly across software, ML, and biology

Competitive base of $200,000–$240,000 , meaningful equity, comprehensive healthcare, generous PTO, and hybrid/remote flexibility

Salary range: $200,000 - $240,000

Foresite Labs is an equal opportunity employer.

We thrive on diversity and collaboration.

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Worksite address

san francisco, CA, 94199, US

Who can apply

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