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Re:Sourced, a Family Office & VC firm focused on US healthcare, is ramping a multi-disciplinary AI software team in NYC. The role centers on building production AI agents, data pipelines and LLM workflows that operate inside live clinical and operational workflows.
You’ll own architecture, deliver production-grade AI solutions, prototype rapidly, and lead technical rollouts across a growing healthcare portfolio. A fast-paced, engineering-led environment awaits.
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A New York firm that owns, operates and invests in healthcare, with billions under management, 200+ operating businesses, and a philosophy of adding value through technology. The portfolio spans skilled nursing facilities, primary care and private medical centres to dental, vision, specialist psychological facilities, and one of the largest long term care pharmacies in the US.
Healthcare runs on administrative loops that nobody has automated properly. A claim gets submitted and comes back rejected. Someone reads the code, works out what's missing, resubmits, chases, waits, repeats. The same shape of loop shows up in pharmacy operations, in scheduling, in every corner of the business. It is one of the largest cost centres in US healthcare and it is still mostly people in back offices.
That is the category of problem this team builds in. Agents that act inside operational workflows rather than generating outputs for someone else to action. The systems have to hold up across different payers, states and facility types, which is where the engineering gets interesting.
The team works "show me, don't tell me." You prototype quickly to find what works, put it in front of someone, then take the winning approach to production. The CTO still writes code daily, so the pace is set from the top.
Python, TypeScript, React, AWS, LLM orchestration, agent frameworks, MCP and data pipelines. Claude Code and Cursor are the primary daily tools.
6+ years shipping production software with deep architecture skill, and startup experience taking something from zero. You prototype to find the answer instead of gathering requirements and thinking about it. You move fast, because the person reviewing your work does.
Production experience with LLMs and agents, including evaluation, guardrails and observability. Fluent across Python, TypeScript, React and AWS, with AI built into how you work every day.
This is a software engineering role at its core. Research depth in model training is welcome but isn't what you'll be measured on. What counts is engineering craft, speed from idea to something running, and whether operators keep using what you ship.
2 rounds. A call with the CTO to confirm fit, then an onsite with the team. No live coding.
Confidential brief available on request.