The role
- COMP
- $160K - $200K
- EQUITY
- 0.20-0.50%
- LOCATION
- San Francisco
- WORKPLACE
- On-site
- EXPERIENCE
- 3+ years
- VISA
- None
- STACK
- Python
- INDUSTRY
- Healthcare, AI, Fintech
/roles — ROLE_391
Founding Engineer, Backend & Infra
Seed-stage healthcare AI company automating the paperwork behind claims, authorizations, and payments between payers and providers
The company
A seed-stage healthcare AI company that reads clinical and billing records to cut administrative work between payers and providers, from claims and prior authorizations to denials and appeals.
- STAGE
- Series A-stage
- FUNDING
- $6M raised
- TEAM
- founding team of <10
- FOUNDED
- 2025
- BACKING
- VC-backed
JD — the work
About the role
You would own and grow the distributed systems at the core of the company's clinical AI platform, from ingesting charts and processing claims to browser automation that works through payer portals. The data is enormous and messy, with page volumes in the hundreds of thousands, and you would design the backend architecture end to end alongside the CEO and a founding team with big-tech and top-university AI backgrounds. It suits someone who thinks in systems and has already held significant ownership at an organization with a reputation for excellent engineering.
What you'll do
- Grow the distributed backend that handles chart data, claims, prior authorizations, denials, and integrations with payers and providers
- Run the agents that operate browsers and desktop software to get through EHRs and payer websites
- Design dependable systems for chaotic inputs such as scanned records, PDFs, claim files, free-text notes, and workflow state
- Create the orchestration, queues, retry logic, and monitoring for long, fragile jobs that span payer systems, clearinghouses, and EHRs
- Work alongside product engineers and researchers to ship new clinical AI features, setting conventions later hires will follow
What they're looking for
- 3+ years of backend or infrastructure engineering experience
- Real ownership of a large area at an organization known for strong engineering
- Ability to design and build complex backend architecture end to end with little guidance
- Comfort with Python and with unreliable, long-running workloads at high volume
- Readiness to work on-site in San Francisco