AI Product Engineer

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)

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.

• 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, Type Script, 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

• 2–8 years of software engineering experience
• Strong backend engineering fundamentals
• Strong Python proficiency
• Frontend experience with React / Type Script
• 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

• 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 Dev Ops 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

• 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

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.