Agent Engineer

About the Role

This role sits at the core of an early-stage healthtech marketplace, owning the agent infrastructure that powers both patient-facing and internal AI systems. You will design and build the orchestration layer, tool integrations, retrieval pipelines, and evaluation frameworks that automate clinic-side and internal operations end-to-end. This is a systems and infrastructure role, distinct from live conversation AI work, and your output will directly shape how the company scales.

What You'll Do

Design and implement the orchestration layer for multi-step agentic workflows across clinic operations and internal processes. Integrate external tools and APIs into agent systems, ensuring reliable tool calling and robust error handling. Build retrieval and evaluation infrastructure to measure and continuously improve agent reliability and accuracy. Identify recurring manual workflows and ship automation systems to eliminate them. Monitor agent performance in production and iterate on system design based on real-world behavior.

What We're Looking For

Demonstrated experience building agent or LLM systems through professional work, personal projects, research, or open-source contributions, covering areas such as orchestration, tool integrations, RAG, or evals. Strong math and computer science fundamentals, evidenced by an elite academic record, competition experience, or fast self-directed learning in technical domains. Experience designing and implementing agent orchestration systems or multi-step workflows.

Experience integrating tools, APIs, or external services into agent systems. Experience building or working with retrieval-augmented generation (RAG) systems. Experience designing evaluation frameworks or monitoring systems for agent reliability.

An automation instinct: you naturally spot recurring manual work and think in systems. Ability to work effectively in a small, early-stage team with limited resources. Bonus: experience with healthcare or regulated industry systems, prompt engineering, LLM fine-tuning, or open-source AI contributions.

No prior professional experience required; recent graduates and self-taught builders are welcome. Compensation & Benefits Base salary of $150,000 to $200,000 annually, plus meaningful equity. Visa sponsorship is not available.

Location Full-time, on-site in San Francisco, California , five days per week.

ABOUT THE ROLE

This role sits at the core of an early-stage healthtech marketplace, owning the agent infrastructure that powers both patient-facing and internal AI systems. You will design and build the orchestration layer, tool integrations, retrieval pipelines, and evaluation frameworks that automate clinic-side and internal operations end-to-end. This is a systems and infrastructure role, distinct from live conversation AI work, and your output will directly shape how the company scales.

WHAT YOU'LL DO

• Design and implement the orchestration layer for multi-step agentic workflows across clinic operations and internal processes.
• Integrate external tools and APIs into agent systems, ensuring reliable tool calling and robust error handling.
• Build retrieval and evaluation infrastructure to measure and continuously improve agent reliability and accuracy.
• Identify recurring manual workflows and ship automation systems to eliminate them.
• Monitor agent performance in production and iterate on system design based on real-world behavior.

WHAT WE'RE LOOKING FOR

• Demonstrated experience building agent or LLM systems through professional work, personal projects, research, or open-source contributions, covering areas such as orchestration, tool integrations, RAG, or evals.
• Strong math and computer science fundamentals, evidenced by an elite academic record, competition experience, or fast self-directed learning in technical domains.
• Experience designing and implementing agent orchestration systems or multi-step workflows.
• Experience integrating tools, APIs, or external services into agent systems.
• Experience building or working with retrieval-augmented generation (RAG) systems.
• Experience designing evaluation frameworks or monitoring systems for agent reliability.
• An automation instinct: you naturally spot recurring manual work and think in systems.
• Ability to work effectively in a small, early-stage team with limited resources.
• Bonus: experience with healthcare or regulated industry systems, prompt engineering, LLM fine-tuning, or open-source AI contributions.
• No prior professional experience required; recent graduates and self-taught builders are welcome. COMPENSATION & BENEFITS Base salary of $150,000 to $200,000 annually, plus meaningful equity. Visa sponsorship is not available. LOCATION Full-time, on-site in San Francisco, California, five days per week.