AI Product Engineer

Location: San Francisco, CA (Hybrid – SoMa, 3 days/week onsite)
Company Stage of Funding: Series B
Office Type: Hybrid
Salary: $160,000 – $260,000 + Competitive Equity
Visa: Full sponsorship supported (including new H1B transfers)

Company Description

Our client is building AI infrastructure for healthcare systems, enabling hospitals and clinicians to deploy reliable clinical reasoning agents at scale.

Their platform powers agentic healthcare workflows used by major health systems including Mayo Clinic and Cleveland Clinic, helping clinicians automate operational and clinical decision-making tasks that directly improve patient outcomes.

The company recently closed a major Series B led by Sequoia and Khosla Ventures, has grown from $200K to $10M ARR within a year, and is rapidly scaling both engineering and product capabilities.

This is an opportunity to join a high-caliber AI product engineering team building mission-critical healthcare AI systems with direct real-world patient impact.

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What You Will Do

Own product features end-to-end from ideation through deployment

Build and scale agentic AI workflows for healthcare systems

Develop backend-heavy infrastructure for clinical reasoning systems

Work across Python, Rust, React, TypeScript, Kubernetes, and AWS

Build reliable long-running agent workflows

Design and implement agent primitives and orchestration systems

Develop scalable backend infrastructure for AI-powered healthcare products

Contribute to frontend product experiences and user-facing tooling

Collaborate directly with clinicians and healthcare stakeholders

Translate user problems into production-ready AI systems

Work across infrastructure, product engineering, and AI systems

Improve reliability, scalability, and operational performance

Participate in technical architecture and product decision-making

Operate in a highly autonomous engineering environment with no PM layer

Build net-new healthcare AI features with strong product ownership

Contribute to async-first engineering workflows

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Ideal Candidate Background

2–8 years of software engineering experience

Strong backend engineering fundamentals

Strong Python proficiency

Frontend experience with React / TypeScript

Experience shipping production-grade software systems

Product-minded engineering approach

Experience with AI agents or LLM-powered workflows

Strong ownership mentality

Ability to operate autonomously

Comfort working in fast-moving startup environments

Strong system design and architecture thinking

Ability to balance technical quality with execution speed

Experience collaborating directly with users or customers

Strong communication and product intuition

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Strong Signals

Top-tier CS program (Stanford, MIT, Caltech, etc.)

Rapid career progression

Founding engineer or early startup employee experience

Experience at high-bar engineering companies

Healthcare or health-tech experience

Agentic workflow experience

LLM systems experience

Backend infrastructure ownership

Experience building production AI systems

Strong product engineering instincts

High ownership and reliability

Async-first work style

Infrastructure and DevOps familiarity

Kubernetes / AWS experience

Rust familiarity

Ability to work without PM structure

Customer-facing product ownership

Experience working closely with clinicians or healthcare workflows

Strong technical depth combined with product thinking

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Compensation and Benefits

Base salary: $160,000 – $260,000

Competitive equity package

Series B growth-stage upside

Visa sponsorship support

Relocation assistance available

Hybrid SF work environment

High ownership engineering culture

Direct customer impact

Work alongside elite engineering and healthcare talent

Async-first, low-meeting culture

End-to-end product ownership

Opportunity to work on mission-critical healthcare AI systems

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Why Join

This is an opportunity to build AI systems that directly impact patient care at scale.

You’ll work on frontier healthcare AI problems involving clinical reasoning, agentic workflows, and production-grade reliability for major hospital systems.

The engineering culture emphasizes ownership, autonomy, and deep product thinking — engineers own the full lifecycle of what they build.

If you want to work on meaningful AI infrastructure, operate with high autonomy, and help define the future of healthcare AI products, this role offers exceptional leverage and impact.