foundationhealthcareers - Product Manager

Remote - United States1w ago

Requirements

• Real builders — founders very welcome. People whose track record is 0-1: spotting the problem, doing the messy early discovery, shaping the product, shipping it to real users, and owning what happened next. If you've started something yourself — even if the mission's now done and you're hunting for that blank-page energy again — you'll fit right in. • People who've shipped AI products, not just used AI tools. There's a big difference between building automations with a classification layer and owning an AI product end to end. You don't need to be an engineer, but you should be able to hold your own on the technical trade-offs — why prompting vs fine-tuning, where explainability matters, what actually caps model performance — and talk honestly about the guardrails you built and what went wrong along the way. • People who work AI-first themselves. If AI is already stitched into how you run your own day — drafting, triaging, spec review, whatever you've rigged up — you'll recognise how we work. We care less about which tools and more that you're the kind of person who keeps pushing what they can do. • People used to startup pace. If you've worked somewhere that ships in days and weeks rather than quarters, you already know the rhythm here. Speed with judgement, not speed instead of it. • Product people, not delivery people. A quick gut-check: plenty of CVs show 10+ years of "product experience" that, on closer inspection, is mostly data flow and integration work — coordinating systems, translating requirements other people wrote. That's valuable work, but it's not this job, and you'd find it frustrating here. If your track record is owning direction and outcomes, you'll love it. • The genuinely curious. Pharmacy is messy, regulated, and full of problems that don't yield to a framework — which is exactly what makes it fun. Deep healthcare experience is a real advantage here — if refills, prior auth, revenue cycle or EHR workflows (Epic, Cerner, FHIR) are home turf for you, you'll add leverage from day one. But it's not a hard requirement: if you've built in an adjacent corner of healthcare, or you're sharp enough to ramp fast and curious enough to have poked around before we speak, that works too. • People who can go deep and zoom out. Detail matters here — but so does pulling out the one or two things that actually matter, building those first, and flexing how you communicate depending on who's in the room. The PMs who succeed here are trusted by clinicians, ops and engineers alike — because they distil, they don't dump. • If you've read this far and thought "that's me" — we'd love to hear from you. Tell us about the best AI product you've shipped when you apply.

Benefits

• Most PM roles at this stage hand you a feature and a roadmap someone else wrote. This one doesn't. • You'll own real product direction — the kind of ownership that's hard to find until you've done another five years somewhere bigger. You'll take genuinely ambiguous problems ("patients keep dropping off between prescription and refill — fix it") and decide what gets built and why. And because we're an AI-first company shipping AI products into production healthcare environments, you'll be working on some of the most interesting product problems going: where do models help, where do they fail, and how do you earn patient and clinician trust around them? • If you've already shipped AI products — taken something powered by LLMs or ML from zero through to real users, made the hard calls, learned from what happened — this is the place where that experience compounds. You won't be evangelising AI to a sceptical org; it's the foundation of everything we build. • What you'll actually do • Own product direction across a slice of our ecosystem — from patient-facing experiences to AI-driven workflow automation for pharmacy teams • Take things 0-1: real discovery with customers and clinicians, scrappy MVPs, buy-vs-build calls, validation before you build and staged rollouts after — then shipped product, quickly. Our cycle times are short and your decisions ship • Decide where AI belongs and where it doesn't — scoping agents properly, defaulting to human-in-the-loop where clinical safety demands it, and making sure things fail safely when they fail • Sit at the centre of engineering constraints, customer expectations and leadership trade-offs — and show up with concrete options, not escalations • Work daily with Engineering and Design; you'll be in the detail, not above it • Make the business case, not just the product case — the best PMs here can put numbers behind "why this, why now" • Challenge how we do things — we're young enough that good ideas get built quickly, and there's real room to shape how product gets done as the team grows