Summary
✨ AI‑Generated
An innovative healthcare technology team is seeking a product engineer to transform AI capabilities into practical user experiences. The role combines frontend and backend development to create applications that improve operational workflows.
Highlights
Build AI-powered healthcare applications while working across frontend, backend, and product engineering challenges in a collaborative environment.
Description
This is a full-stack application engineering role within Clients Lab, the company's AI innovation engine The team is building an AI-native Healthcare Revenue Operating System that automates medical coding, billing, and claims follow-up across 95 of the top 100 U.S.
health systems.
The Product Engineer builds the user-facing application layer that translates AI model outputs into usable healthcare workflow interfaces.
Day-to-day work is writing React frontends, Node.js services, and Python integrations that make AI-generated insights — coding recommendations, claim adjudication, denial management — accessible and actionable for healthcare operations teams.
Must be based in the New York, San Francisco, or Austin metropolitan area and within commuting distance of the respective hub as this is a hybrid role.
React experience must be demonstrated through actual project/work experience, along with broad, user-focused engineering contributions.
Required technical skills
5+ years exp
Primary stack: React, TypeScript, Node.js, SQL, Python
AI/ML outputs are consumed, not built — the Product Engineer surfaces AI outputs for users, not trains models.
Phare OS / Phare Flow application
Cloud platform
CI/CD and deployment: the Data Platform team (separate role)builds CI/CD pipelines from scratch.
Product Engineers likely deploy through shared infrastructure
Full-stack engineering capability across React, TypeScript, Node.js, and Python.
[Demonstrated ability to own features end-to-end — from scoping and requirements through implementation to deployment.
User-centered design thinking demonstrated in engineering work.
Candidates must show evidence of considering end-user needs in how they build, not just what they build.
This is the 1 evaluation criterion in the interview.
Preferred
Experience building user-facing applications on top of AI/ML outputs — translating model results into actionable product interfaces.
Healthcare revenue cycle, billing, or clinical workflow experience.
Visual design skills (Figma, Illustrator
Experience working in fast-moving startup or research-to-production environments.
Prototyping mindset
