AI Product Engineer
Job description
AI Product Engineer at Bunkerhill Health.
About the role
This role focuses on end-to-end ownership of product features in a high-volume healthcare setting. You will work at the intersection of product and engineering, solving diverse technical problems while delivering software that affects patient outcomes.
Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.
Key facts
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Location: SF
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Engagement: Full-time
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Compensation: equity, comprehensive benefits (medical, dental, vision, commuter, and 401(k))
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Team: works with clinicians, end users, and non-technical members
- Years: 2+
- Visa: none stated
- Degree: a degree in Computer Science or a related field is required
What you'll do
Features are owned end-to-end, from ideation and design through implementation, testing, and deployment in agentic workflows at scale.
New tools and processes are suggested based on emerging technologies, and collaboration across disciplines translates goals from clinicians and end users into clear, actionable solutions. Deep intuition about the product is developed through direct interaction with the system and its users.
Requirements
Full-time software engineering experience spans 2+ years in professional roles. A Bachelor's or advanced degree in Computer Science or a related field is required. Adaptation to new languages, frameworks, and technologies is demonstrated through problem-solving, analytical work, and communication. Proficiency in at least one backend language is necessary, with Python and Rust forming the primary stack. Comfort using AI coding tools and willingness to learn about agentic workflows are expected.
Practical notes
The office is in SoMa, San Francisco, with a schedule of four days in the office per week. Typical interview steps
Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.
Good to know
Work in this field centers on applying technology to healthcare outcomes using Python and Rust. Agentic workflows and infrastructure tooling such as Kubernetes, Terraform, and frontend frameworks are common in this type of role.
Questions to ask
Useful questions for the interview: what a typical week looks like, how work is assigned, what tools the team uses, and how feedback works. Asking how the role has changed recently and what the team wishes it had known when joining is also reasonable. Questions about the manager's priorities are especially valued.
Career growth
Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.
About the company
Bunkerhill helps health systems use generative AI to understand each patient's full clinical context and take the right next steps - automatically and at scale.