Quality Assurance Engineer
2 days ago
Braintree
Company Description Our client is an enterprise software business delivering Electronic Document Management Systems and Agentic AI-driven care pathway solutions into UK healthcare. They hold a market-leading position in EDMS and is at the forefront of advancing digital maturity across NHS Trusts. Role This is a hands-on QA engineering role focused on automation, data quality, and real world clinical scenarios. You will be responsible for ensuring the reliability and quality of systems that ingest, process, and surface large and complex clinical documentation at scale. You will: • Build and maintain robust automated test coverage across UI, API, and data pipelines, • Apply risk based exploratory testing to complex real world healthcare scenarios, • Use AI tools such as Cursor and agents to accelerate test creation, analysis, and defect investigation • Ensure clinical relevance and signal quality in testing, not just technical correctness This is not a test execution role. You are expected to think like an engineer, a user, and a risk owner. Responsibilities Automation and Engineering Quality • Design, build, and maintain automated test suites across UI, API, integration, and regression within CI CD pipelines • Ensure test suites are fast, reliable, and provide high quality signal, • Reduce flaky tests and improve failure diagnostics Clinical Data and Scenario Based Testing • Validate system behaviour against real world NHS data patterns, including:, • Large patient records, • Mixed structured and unstructured clinical content, • Variable document quality and formats, • Ensure key clinical information is correctly surfaced and not lost in volume or noise, • Test edge cases driven by data scale, duplication, and inconsistency, • Test system behaviour under high data volume conditions, ensuring performance, accuracy, and usability at scale AI First QA Practices • Use AI tools such as Cursor and agents to: o Generate and refactor test code o Create edge case scenarios based on real data patterns o Accelerate defect triage and root cause analysis o Support generation of release evidence • Critically review all AI generated outputs and maintain human accountability Essential: • Proven experience in modern QA engineering with strong automation ownership, • Hands on experience with JavaScript or TypeScript testing frameworks such as Cypress or Playwright • Experience testing APIs and backend services, • Experience integrating automated tests into CI CD pipelines, • Experience working with large and complex datasets, ideally document heavy systems, • Practical experience using AI coding assistants or tools in delivery workflows, • Strong defect investigation and root cause analysis skills, • Ability to define, measure, and communicate quality effectively, • Strong cross functional collaboration skills Desirable: • Experience in healthcare, NHS, or regulated environments, • Understanding of unstructured data, document management, or EDMS systems, • Experience with risk-based testing and traceability models, • Familiarity with test data management and environment strategy, • Exposure to performance, security, or accessibility testing, • Experience with Jira, test management tools, and quality dashboards