Principal Software Engineer

About Foundation Health

Foundation Health is an AI operating system for pharmacy - built by a team who lived the problem firsthand, not one that came to healthcare from the outside. Every day, prior authorizations delay prescriptions, pharmacists lose hours to paperwork instead of patients, and prescriptions slip through the cracks between health systems. We believe thoughtfully applied AI can finally change that - deep, integrated infrastructure that streamlines how care is coordinated, purpose-built for the complexity of specialty pharmacy.

We're building toward a world where pharmacy teams spend their time on patients, not paperwork - where AI handles the routine so clinicians can focus on what only humans can do. Getting there takes the right people. We're looking for curious, ambitious folks who want to help solve healthcare's hardest problems - for our patients, our partners, and each other.

The Role

This isn't a pitch deck. Our platform is live in production inside major US health systems — including Intermountain Health — where our AI handles real patient communication over voice and SMS and plugs directly into Epic workflows. We have a public partnership with Amazon Pharmacy. We raised a $20M Series A led by Define Ventures. Our CEO is a 2x founder; our VP of Engineering came from DeepMind. We're ~70 people, past PMF, with enterprise customers pulling us forward faster than we can hire.

You'll own architecture across multiple product areas, designing systems that can support 10–100x growth without a rewrite. But when the hardest problem in the company needs solving, you're the one who opens the editor and builds the first version. If your last few years have been slide decks and steering committees, this isn't the role. If you've been the person who prototyped the thing everyone said was impossible, keep reading.

You'll work directly with our VP of Engineering and CEO — but nobody here manages from a distance, at any level, and the Principal is no exception.

The technical problems you'd own

• Agentic AI in a regulated environment: voice and SMS agents interacting with real patients, with the evals, guardrails and pharmacist-oversight architecture that makes that safe. This is the hard version of applied AI — the version where "it hallucinated" isn't a funny screenshot

• Deep EHR integration: Epic queues, prior authorization automation, 340B compliance — systems where correctness genuinely matters and the specs were written before you graduated

• Target-state architecture for the platform as it scales from a handful of health systems to hundreds — and building the first mile of the migration yourself

• Our AI engineering itself: model selection, context management, cost/latency tradeoffs, evaluation methodology

What we're looking for

• A deep engineering background is non-negotiable. You've built serious systems with your own hands, recently — not managed people who did — and you can go toe-to-toe on the details of anything you've shipped

• You've operated at Staff+ level somewhere with a genuinely high bar, and can point at architectural decisions a company still runs on

• Hands-on fluency with applied AI — you've built with LLMs in production, not just read about them

• High agency. You find the highest-leverage problem in the org and go solve it — nobody points you at it

The practical stuff

We're remote-first across the US, though we've just opened a hub in Orlando if you ever wanted your comp to survive contact with your cost of living. And it's early enough that the equity is founding-role equity, not a rounding error.