SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: GBP 80,000 - 115,000 / annual
AccuRx is a digital healthcare platform used by 98% of UK GP practices, enabling communication between clinicians, staff, and patients across the NHS. The company has evolved from GP-to-patient texting into a comprehensive toolkit including 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 Senior Product Engineer, you will own features end-to-end—from problem refinement with clinicians and product managers 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 architecture and API boundaries with the broader system in mind, hold the quality bar for shipping reliable and safe clinical products, make architectural decisions that keep the codebase sustainable, and push back constructively when something is wrong.
The engineering stack is primarily C# (backend), TypeScript and React (frontend), running on Azure, with Python for ML/AI work. You'll be expected to follow problems across the full stack to own features end-to-end, though you may have a strongest area.
The team values engineers who have sat in GP waiting rooms and understand the real friction points. Product Engineers here shape what gets built and how, working with Product, Design, and Clinical from the earliest stages, and stay with systems as they evolve. You'll bring engineering judgment into product decisions and product thinking into engineering ones.
Requirements:
- Comfortable building production software across the stack (backend or frontend strength acceptable, but must follow problems 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, push for right architectural decisions under real constraints
- Curiosity about AI tools and how they change your work, with judgment to know when to rely on them and when not to
- Start from user problems, not 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; understand what "great" looks like in your domain and reliably get there
- Own outcomes, not just tasks; influence across teams, navigate disagreement, own mistakes, push for wins that matter
- Actively experiment with AI tools with healthy scepticism about what they can do
