The WorkThe core challenges are data complexity and reliability under extreme variability.
You can think about it as reverse-engineering the back office of every healthcare facility in the U.S., then rebuilding it as a system that continuously learns from outcomes and improves across thousands of edge cases.
That includes:
- Building agentic systems that run end to end across fax, email, web portals, and physical mail, where each document type triggers a different workflow.
- Processing records that average 300 pages, sometimes hit 30,000, and run roughly 70% duplicate, and still surfacing what matters to a case.
- Matching patients and facilities across messy provider networks, where a single system like NYU Langone is 340+ care locations with no clean way to match them.
We9re a lean team where everyone works on everything. The work splits loosely across automating the retrieval pipeline, the customer-facing product law firms use to request and view records, and the applied AI threaded through both.
You9ll move between them as our goals shift, ship customer-facing product one month and go deep on the pipeline the next, and stay close to both the customer and the data.
Who we9re looking forThis role is open at all levels. You might be a fit if you:
- Have shipped features start to finish in production and want to own outcomes.
- Go deep on the domain: the data systems and the workflows our agents run.
- You9ve explored LLMs and are excited about turning them into reliable systems.
- Want to talk to users directly and ship off their feedback.
- Are excited to apply real engineering rigor to a messy, economically valuable problem.
You9d work directly with the founders and a small, high-bar engineering team.
Non-negotiableFully in person in Dumbo, Brooklyn.
StackTypeScript and React on the frontend. Python and FastAPI on the backend.
CompensationCompetitive base salary, early-stage equity, unlimited PTO, and benefits.
