Quality Assurance Engineer (m/f/d)

Job description

Your career oportunity (from 15.09.2026) You combine strong, hands-on software testing skills with a practical understanding of AI-driven product features and modern AI-supported QA workflows? Also you like to ensure reliable releases across web and/or backend systems, while also contributing to quality strategies for AI-enabled functionality? Then this position might be the perfect fit for you! Your Mission You own our test strategy end-to-end —and you continuously improve it across both manual and automated testing as we grow. You design, execute, and maintain test cases that cover new features, regressions, and the “it’ll never happen” edge cases. You build reliable automated tests (E2E and API) and you keep them healthy in CI/CD —stable, meaningful, and easy to maintain. You partner closely with Product and Engineering to clarify requirements early, tighten acceptance criteria, and prevent defects before they ship. You define quality signals and metrics that create real release confidence —not just a gut feeling. You raise the bar for AI-feature quality where relevant, including: - You test robustness across varied inputs (ambiguous prompts, noisy data, unexpected user behavior). - You check safety, privacy, and unintended outputs in line with product requirements. Requirements Your Superpowers Your Superpowers You’ve worked in software testing / QA engineering in cross-functional teams and you know what great collaboration looks like. You’re strong in test design, exploratory testing, and defect investigation —you enjoy finding root causes, not just symptoms. You have solid hands-on experience with test automation (e.g., Playwright, Cypress, Selenium) and API testing (e.g., Postman, Bruno). You’re comfortable with CI/CD and version control (e.g., Git and GitHub/GitLab pipelines) and you treat testing as part of delivery. You understand modern software delivery practices like shift-left QA, code reviews, observability, and documentation—and you apply them pragmatically. You have working knowledge of AI/ML or LLM-powered features and you can translate that into practical quality checks. You communicate clearly and think pragmatically —you balance quality, speed, and risk to help the team ship responsibly. Nice to Have You’ve tested AI/LLM features before (prompt variations, guardrails, unexpected outputs, evaluation approaches). You bring exposure to per…