QA and Validation Engineer — Engineering Software

About the role

This person will work on the quality of the WDT and R&D projects, focusing on functional, regression, integration and end-to-end tests, calculation validation, benchmarks and evidence for TRL progression. The role is broader than manual testing: complex engineering workflows must work, remain traceable and have clear acceptance criteria.

The WDT combines software, 3D models, inspections, risk, sensors, simulations, AI and assisted operation. Quality needs to cover the whole path: requirement, input data, expected behavior, evidence, defect, fix and documentation.

Main responsibilities

• Plan and run functional, regression, integration, end-to-end and applied validation tests on WDT modules.
• Create traceability matrices linking requirements, tests, evidence, defects and acceptance criteria.
• Validate inspection, document, risk, degradation, sensor, AI, FEA, dashboard and offline-operation workflows when they apply.
• Support calculation benchmarks, result comparison and tests of robustness, usability and performance.
• Automate frontend, backend and API tests whenever that is appropriate.
• Organize technical evidence for pilots, demonstrations, internal audits and R&D milestones.
• Work with development, engineering, product, DevOps and security to prioritize fixes and risks.

Required qualifications

• Experience in software QA, functional validation or testing of complex systems.
• Knowledge of API, frontend, backend and regression testing and of defect documentation.
• Ability to write clear, reproducible test scenarios connected to requirements.
• Attention to evidence, traceability, acceptance criteria and objective communication.
• Familiarity with Git, issue tracking, acceptance environments and release cycles.
• Interest in engineering software, digital twins, technical data or simulations.

Preferred qualifications

• Experience with Playwright, Cypress, Selenium, Postman or test automation.
• Background in Azure DevOps, pipelines, end-to-end tests and validation in cloud environments.
• Knowledge of FEA, engineering calculations, inspections, risk, sensors or AI applied to QA.
• Experience with evidence for TRL, technical audit, pilots or demonstrations.

Related technologies and tools

Playwright, Cypress, Selenium, Postman, API tests, end-to-end tests, Azure DevOps and evidence documentation.

Profile

We are looking for a careful, practical and curious person who can test beyond the happy path. They should be able to talk with engineering and software, document well and turn defects into product learning.

How to apply

To apply, send the following materials:

How do you currently use artificial-intelligence tools in your professional workflow? Name the tools, give examples of activities, and explain how you validate the results produced with AI assistance.

Additional information may include LinkedIn, GitHub, Behance, Google Scholar, articles, publications, websites, demonstrations, applications or other links relevant to the role.

• An up-to-date curriculum vitae with education, professional experience, main projects, technologies used and responsibilities held.
• A portfolio with concrete examples of previous work. For software, this may be GitHub, applications, systems, APIs, interfaces or projects that can be demonstrated. For engineering, this may be models, simulations, reports, analyses, publications or technical work that can be shared. Confidential projects may be presented in anonymized form.
• A presentation video of up to 5 minutes, briefly showing a project or portfolio, the problem solved, your contribution, the technologies used, your working workflow, everyday tools, your use of artificial intelligence and how you validate results produced with AI support.