Software Engineer
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Posted within 60 days ·
- Work arrangement
- hybrid
- Employment
- FullTime
- Stated compensation
- Not specified
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1 with evidence8 unclear or unstated- Remote policy
- hybrid
“Provider workplace type: hybrid”
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- FullTime
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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 team: AI-native by design
Our VP of Engineering comes from DeepMind/Google, and we're building with AI from day one, both in the product and in how we engineer. We use AI tools to move faster, automate repetitive work and spend more time on problems that need real engineering judgement.
What you'll actually be doing
Designing and building the back-end systems that connect pharmacies, health systems and insurers
Solving hard distributed-systems problems: event-driven workflows, retries, idempotency, data consistency and failure recovery
Owning substantial features from the initial problem through architecture, build, deployment and production
Making pragmatic technical decisions as we scale, without overengineering for problems we don't have yet
Building AI-powered capabilities into a live product, where reliability and correctness matter as much as speed
Working directly with product and engineering leadership to shape the roadmap, architecture and what we build next
Manchester: where our core engineering team works
Our core engineering team is based in Manchester city centre. We're in the office together 1–2 days a week to work through hard problems and debate technical decisions. The rest of the week, work wherever you're most effective.
Not in Manchester yet? If you'd consider relocating, we can help with the move.
Why you'd leave your current role
Your work reaches real users. We're live with enterprise customers, so what you ship gets used, not lost in a backlog.
Interesting engineering problems. We're connecting fragmented healthcare systems, where data integrity and correctness really matter. This isn't a CRUD app with an AI feature bolted on.
Real ownership. You'll shape solutions, challenge assumptions and influence the roadmap and architecture. We want you making important technical decisions, not just implementing someone else's.
No legacy baggage. We're on a modern Node.js, TypeScript and GCP stack. You don't need to know it already. We care far more about the systems you've built than the tools you used.
Equity. You'll own a stake in the company you're helping build.
What we do care about
Strong engineering judgement. You can take an ambiguous problem, work out what matters, make sensible trade-offs and deliver without every step mapped out.
Back-end depth. You've built and operated production systems and know what happens beyond the happy path: distributed systems, databases, performance, observability and failure recovery.
Ownership beyond the code. You think about how a feature behaves in production, how customers use it and what could go wrong. You've made technical decisions with real consequences and can explain why you made them.
A builder's mindset. You've taken meaningful projects from idea to reality, at work or in your own time, and can explain the decisions and trade-offs you made.
Curiosity about AI. You've built AI products, use AI to improve how you work, or are actively exploring what's possible. You don't need to be an ML researcher.
Strong fundamentals. You reason from first principles and pick up unfamiliar tech quickly. A degree in Computer Science, Maths, Physics or Engineering is useful, but depth of engineering ability matters most.
Interested?
The funding's in place, the product is live and customers are asking for more than we can build. We're hiring engineers in Manchester to help close that gap.
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