Full Stack Engineer

SAH Diagnostics; West of England; On-site; GBP 60,000 - 90,000; Full time

Job summary

SAH Diagnostics, an NHS partner, seeks a software QA engineer to design, build, and test features across our platform, including automated E2E tests and CV/ML components for cancer detection. You will collaborate with product, clinical, and engineering teams to deliver production-ready features, work on MFA, login, and onboarding flows, and ensure secure healthcare data handling.

This office-based role at UWE Bristol offers a permanent full-time position with opportunities to advance in a

Qualifications

• Experience designing and executing automated E2E tests.
• Proficiency in Python, ML/CV frameworks, and medical imaging.
• Experience in secure coding and healthcare data workflows.
• Ability to work independently with minimal supervision.

Responsibilities

• Develop and maintain automated E2E test suites (Cypress, TS) for MFA, login and onboarding.
• Implement and debug authentication logic including MFA enrolment and verification.
• Build computer vision models for medical imaging, including cancer detection.
• Integrate ML models into clinical apps using Python and PyTorch.
• Collaborate with backend engineers to validate API behavior and security.
• Ensure reliability with regression testing, CI pipelines and robust error handling.
• Translate medical requirements into CV/ML solutions with clinicians.

Skills

End-to-end testing

Independent worker

Problem solving

Tools

TypeScript

Cypress

Python

PyTorch

OpenCV

ML model development

Job description

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

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 development
• Experience with medical imaging, segmentation, classification, or anomaly detection.
• 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.