Full Stack Engineer

Sah Diagnostics — United Kingdom · Posted ~9 hours ago

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Description

Job Title: Full‑Stack AI Engineer About the Company SAH Diagnostics is a trusted NHS partner delivering end-to-end diagnostic and clinical services that expand capacity, reduce waiting times, and improve patient outcomes across England. We specialise in fully managed insourced and outsourced solutions, supporting NHS Trusts, Integrated Care Boards (ICBs), and Cancer Alliances to meet the 28-day Faster Diagnosis Standard (FDS) and 62-day referral-to-treatment targets—without additional financial burden to the system. Employment Type: Full-Time Location: : This role is office-based at UWE Bristol. Contract Type: Permanent Salary: Competitive Start date: ASAP Role Overview You will design, build, and test features across our platform. This includes writing automated E2E tests, integrating platform features, and developing computer vision models for early detection of cancers and other diseases. You will work closely with product, clinical, and engineering teams to deliver reliable, production‑ready features. Key Responsibilities Develop and maintain automated E2E test suites (Cypress, TypeScript) for critical flows such as MFA, login, onboarding, and clinical workflows.Implement and debug authentication logic including MFA enrolment, verification, and backend probe flows.Build and deploy computer vision models for medical imaging (e.g., cancer detection, anomaly classification).Integrate ML models into clinical applications using Python, PyTorch, and more.Collaborate with backend engineers to validate API behaviour, session handling, and security requirements.Ensure reliability through regression testing, CI pipelines, and robust error handling.Work with clinicians to translate medical requirements into technical CV/ML solutions. Requirements Strong experience with TypeScript, Cypress, automated testing, and E2E test design.Proficiency in Python, PyTorch, OpenCV, and ML model developmentExperience with medical imaging, segmentation, classification, or anomaly detection.Machine Learning 6-12 months experience.Ability to debug backend API behaviour using tools like cy.request, logs, and probe flows.Understanding of secure coding practices and healthcare data workflows.Strong problem‑solving skills and ability to work independently on complex technical tasks. How to apply: Submit your CV to recruitment@sahdiagnostics.com or apply directly on LinkedIn If this sounds like you — or someone you know — please get in touch!