Senior Qa Engineer (m/f/d)

GE Healthcare GE Healthcare · Healthcare · Munich, Bavaria, Germany · Digital Technology / IT

Senior QA Engineer responsible for ensuring the quality, reliability, and safety of complex healthcare software systems, with an emphasis on using generative AI tools to enhance testing activities within a regulated healthcare environment.

What you'd actually do

  1. Define, implement, and continuously improve test strategies for complex software systems
  2. Design, execute, and maintain robust manual and automated test suites
  3. Ensure quality coverage across functional, regression, integration, and system-level testing
  4. Work closely with development and product teams to embed quality early in the design and implementation phases
  5. Use generative AI tools to enhance QA activities (e.g., test design, test data generation, exploratory testing support, log analysis, and documentation), ensuring transparent and policy-compliant usage

Skills

Required

  • Several years of professional experience in software quality assurance or testing
  • Solid experience in manual and automated testing of complex software systems
  • Strong knowledge of testing methodologies, test design techniques, and defect management
  • Experience testing software on Windows and/or Linux platforms
  • Practical experience with test automation frameworks, scripting, or tools
  • Demonstrated experience using generative AI tools to support QA or software development activities
  • Ability to apply risk-based thinking to testing and release decisions
  • Strong analytical skills to assess quality impact on users, products, and business outcomes
  • Takes clear ownership of quality outcomes for assigned products or components
  • Effectively collaborates across engineering, product management, and domain teams
  • Communicates quality risks and trade‑offs with clarity and confidence

Nice to have

  • Bachelor’s degree in Computer Science, Software Engineering, or a related STEM discipline
  • Strong interest in AI‑enabled software and quality challenges in healthcare environments
  • Good understanding of secure and quality‑focused software development practices
  • Proactive in identifying quality gaps and proposing practical improvements
  • Comfortable balancing delivery timelines with quality and compliance expectations
  • Influences teams toward higher quality standards through data, insight, and constructive challenge
  • Mentor less experienced QA team members and support the overall growth of quality engineering capabilities

What the JD emphasized

  • generative AI tools
  • regulated healthcare environment

Other signals

  • use generative AI tools to enhance testing activities
  • quality, reliability, and safety of complex healthcare software systems
  • regulated healthcare environment