Test Automation Engineer

Tasks & Responsibilities: 

• Quality Assurance for High-Tech: Development and implementation of automated test strategies for a complex overall system in molecular diagnostics. 
• BDD Methodology: Active application of Behavior-Driven Development to translate requirements into executable specifications.
• AI-Driven Test Development: Leverage state-of-the-art AI agents and automated generation tools to design, write, and maintain scalable test cases across software, hardware, and assay workflows.
• Development of Test Environments: Construction and maintenance of test frameworks using tools similar to Selenium, Appium, or SpecFlow, supplemented by specific libraries for controlling laboratory robots.
• Robotics Integration: Evaluation and integration of commercial robot arms (e.g., Cobots) as well as participation in the development of internal robotics tools to simulate user interactions on the device (e.g., pipetting, loading cartridges).
• ALM & Traceability: Use of ALM tools such as Codebeamer to manage requirements and test cases and to ensure traceability.
• CI/CD Integration: Responsibility for automated quality assurance within our GitHub repositories and Azure DevOps (ADO) pipelines.
• End-to-End Verification: Ensuring data integrity from the barcode scan of the patient sample to the final analysis of the PCR result.
• Compliance & Documentation: Supporting the creation of test plans, protocols, and reports in accordance with ISO 13485 and other relevant regulatory standards for medical devices.

Must Haves:

• Education: Degree in Computer Science, Electrical Engineering, Medical Technology, or a comparable qualification.
• Technical Expertise: Min. 5 years experience as a Software Engineer in Test (SET) or Test Automation Engineer, ideally within complex mechatronic, medical device, or biotech systems. You have sound experience in software development and master clean coding principles.
• Automation & BDD Expert: Proficient in using modern test automation frameworks, with desired knowledge of behavior driven development methodologies.
• AI Tooling Proficiency: Practical experience using AI coding assistants, LLM agents, or AI-native test management tools to automate, refactor, and maintain testing assets.
• ALM Know-how: Experience with Application Lifecycle Management tools, ideally Codebeamer, is a major advantage.
• Analytical Talent: Ability to familiarize yourself with the logic of complex diagnostic systems.