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Salary: GBP 40,000 - 80,000 / annual
AccuRx is a healthcare communication platform used by 98% of UK GP practices. The company has built an all-in-one digital toolkit that connects NHS staff, GPs, and patients through a single system, replacing fragmented legacy tools. Products include Total Triage (patient demand management), Self-Book (appointment scheduling), Patient Questionnaires (routine care automation), Accumail (staff-to-staff communication), and Accurx Scribe (AI-powered clinical note-taking).
As a Product Engineer, you will own features end-to-end, from problem definition through architecture, implementation, rollout, and long-term evolution. You'll engage directly with NHS GPs, practice staff, and patients to understand the problems you're solving, including research sessions and practice visits. You'll design system architecture and API boundaries with the broader platform in mind, hold quality standards for reliability and safety in a clinical context, and make architectural decisions that keep the codebase sustainable while shipping features. You'll work across the full stack (C# backend, TypeScript/React frontend, Azure infrastructure, Python for ML/AI) and push back constructively when something is wrong.
The engineering team is characterized by deep domain understanding—engineers have sat in GP waiting rooms and watched practice managers juggle multiple systems. What sets Product Engineers apart is that they own the problem, not just the code, shaping what gets built and how by working with Product, Design, and Clinical from the earliest stages.
You'll be joining a fast-growing Tech for Good company with a mission to fix healthcare communication. The role is based in Shoreditch, London, with a hybrid arrangement requiring 3 days per week in the office (core hours 10am–4pm). The team is dog-friendly, and the company provides free healthy meals prepared by an in-house chef.
REQUIREMENTS:
- Comfortable building production software across the full stack; can follow a problem across backend and frontend to own a feature end-to-end
- Proven ability to reason about systems: breaking ambiguous problems into tractable pieces, spotting trade-offs and second-order effects before they become incidents
- Comfortable with ambiguity and early-stage problem definition; you shape the work rather than wait for a finished spec
- Treat engineering quality as part of the job: manage technical debt pragmatically, review AI-generated output critically, and push for the right architectural decisions under real constraints
- Curiosity about AI tools and how they change the way you work, with judgment to know when to rely on them and when not to
- Start from the user problem, not the technology; know what to build, what not to build, and why
- Can pick up unfamiliar code and systems, assess AI-generated output, and spot flaws before being told
- Strong expertise in at least one area (backend, frontend, systems design, etc.) and can use it to build, debug, and improve real systems effectively
- Own outcomes, not just tasks; influence across teams, navigate disagreement, own mistakes, and push hard for wins that matter
- Actively experiment with AI tools to push boundaries, with healthy skepticism about what they can do
