Senior AI Engineer

Family Office & VC Firm | US Healthcare | NYC | Hybrid Environment Follow @Re:Sourced for the latest AI, Software and Data Engineering opportunities Benefits & Why This Opportunity Is Unique: A multi-billion dollar firm that owns, operates and invests in healthcare. 200+ (and growing) operating businesses, with a central engineering team building AI directly into them instead of outsourcing it. The work is agentic systems that take action inside live operations, where being wrong has a cost. Think billing and reimbursement, pharmacy operations, clinical scheduling and dispatch. Because the firm owns the businesses, there is no client to sell to and no procurement cycle. If it works it ships, then it rolls across the portfolio. A product team of ex-consulting operators and senior PMs sits with the businesses and brings you the problem defined, so your time goes on architecture and delivery. Engineering led by the former CTO of one of the world's most successful AI HealthTech companies, alongside engineers from Meta, Netflix, Atlassian, McKinsey and BCG X. You’ll build across a broad range of healthcare operations: primary care, nursing facilities, hospitals, pharma, dental, vision, mental health and more. Solutions that scale can be spun out as standalone HealthTech ventures, with a direct route to VC including the firm's own venture fund, and equity for the engineers who built them. A team of 10, so you sit close to the decisions with genuine technical scope and direct access to leadership. Above-market salary + performance bonus + fund performance bonus + Group ESOP + partnership equity in the HealthTech spin-outs. Purpose-built NYC office, remote Fridays, flexible working hours, regular events and socials. 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. The Opportunity: 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. What You'll Do: Own the architecture: design the system, make the build-versus-reuse calls, and set the patterns the rest of the portfolio inherits. Build and ship production AI systems: agents, LLM workflows, data pipelines, and the evaluation and monitoring around them. Prototype fast to de-risk a problem, then take the approach that works to production. Lead the technical rollout across the portfolio. Work alongside product to pressure-test what's being asked for before you commit to a design. Tech Stack: Python, TypeScript, React, AWS, LLM orchestration, agent frameworks, MCP and data pipelines. Claude Code and Cursor are the primary daily tools. What You Bring: 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. The Process: 2 rounds. A call with the CTO to confirm fit, then an onsite with the team. No live coding. Confidential brief available on request. #J-18808-Ljbffr Re:Sourced.