Job Description

Location: San Francisco, CA — hybrid, 4 days/week in office

Employment: Full-time

Relocation Support: Available

Visa Sponsorship: Available for eligible candidates

About the Company

We’re working with a rapidly growing, venture-backed healthcare AI company building an agentic AI platform used by major health systems.

The company is well-funded, has experienced significant commercial growth, and operates with a small, highly technical team. Engineering is intentionally lean, giving individual engineers substantial ownership over product direction, architecture, and execution.

The Role

The company is hiring several AI Product Engineers to build the infrastructure and product experiences behind reliable, long-running AI agents used in real healthcare workflows.

This is a backend-leaning product engineering role for engineers who enjoy owning problems end-to-end.

There is very little separation between product and engineering. Engineers help understand user problems, decide what should be built, design the architecture, implement the solution, deploy it, and iterate based on real-world usage.

The work is approximately 65% backend / 35% frontend.

The core stack includes Python, React/TypeScript, Kubernetes, AWS, and additional systems languages and infrastructure tools.

What You’ll Do

• Own product features from initial problem discovery through architecture, implementation, deployment, and iteration.
• Build backend infrastructure and primitives for complex agentic AI workflows.
• Design reliable systems for long-running AI processes, including orchestration, state, tool execution, observability, evaluation, and failure handling.
• Build primarily in Python while contributing across the broader product stack.
• Work with React/TypeScript where needed to ship complete user experiences.
• Deploy and operate production systems using Kubernetes and cloud infrastructure.
• Translate ambiguous user and customer needs into practical technical solutions.
• Make product and technical decisions without relying on a PM to define every requirement.
• Work closely with a small, highly autonomous engineering team.

What We’re Looking For

• 2–8 years of professional software engineering experience, ideally 4–6.
• Bachelor’s or advanced degree in Computer Science or a closely related technical field.
• Strong software engineering fundamentals.
• Strong backend development experience.
• Proficiency with Python or another modern backend language such as Go.
• Experience designing and shipping meaningful production systems end-to-end.
• Evidence of high ownership and initiative.
• Strong product judgment and an ability to think about the end-user impact of technical decisions.
• Comfort operating in a fast-moving environment with significant autonomy.
• Willingness to work in-office in San Francisco four days per week.

Strong Candidate Signals

We’re particularly interested in engineers who have demonstrated at least one standout signal in their career, such as:

• Significant impact at a high-bar engineering organization.
• Early or founding engineering experience at a strong venture-backed startup.
• Rapid career progression.
• Ownership of an unusually impactful or widely adopted product or platform.
• Strong academic performance at a highly regarded computer science or engineering program.

Especially Relevant Experience

Any of the following are valuable, but not all are required:

• Agentic AI systems or LLM-powered applications.
• RAG, model orchestration, tool use, or AI evaluation.
• Distributed systems and backend infrastructure.
• Kubernetes, AWS, Helm, or related infrastructure tooling.
• React and TypeScript.
• Healthcare or health-tech.
• Early-stage or rapidly scaling startups.
• Customer-facing or product-oriented engineering.
• Building products with limited PM involvement.

Team & Working Style

The engineering organization is small, flat, and highly autonomous.

Engineers work across the product rather than operating in narrow silos. There are few recurring meetings and a strong emphasis on thoughtful execution, reliability, and individual ownership.

The role involves more than writing code. Engineers are expected to spend meaningful time understanding users, evaluating tradeoffs, planning architecture, reviewing systems, and deciding what should be built.

Interview Process

1. Introductory Interview — 30 minutes
2. Background, motivation, ownership, product thinking, and working style.
3. Coding Challenge — 90 minutes
4. Two production-inspired programming problems.
5. Technical Interview — 60 minutes
6. Coding, technical depth, problem solving, and reasoning.
7. On-Site Interviews — approximately 3 hours
8. Technical ability, system design, product judgment, and collaboration.
9. Final Interview
10. Final conversation with engineering leadership.
11. Reference Checks

Why Consider It

• Build production AI systems solving complex real-world healthcare problems.
• Work on agentic systems rather than simple AI integrations.
• Join a small engineering team where individual contributions have significant impact.
• Own products from initial problem through production.
• Work directly on backend, infrastructure, AI, and product challenges.
• Join a rapidly scaling, well-funded company at an important stage of growth.
• Competitive compensation, equity, relocation support, and visa sponsorship.