AI-nativeQAEngineer

## Accountabilities You will be responsible for building and evolving AI-powered QA systems that ensure product quality across complex, fast-changing workflows. Your role will combine automation engineering, testing strategy, and AI-driven experimentation. Design and build AI-assisted testing frameworks and pipelines covering functional, regression, integration, and performance testing. Develop and maintain automated test suites integrated into CI/CD pipelines using modern engineering practices. Leverage LLMs and AI tools to generate test cases, analyze defects, and accelerate QA workflows. Perform root cause analysis of bugs and production incidents, identifying patterns and preventing regressions. Collaborate closely with developers, product managers, and R&D teams to validate releases and ensure system reliability. Improve test coverage, QA processes, and automation frameworks continuously through data-driven insights. Support validation of agent-based or AI-driven systems and ensure robustness of complex workflows. Requirements The ideal candidate is a technically strong QA engineer with deep automation experience and hands-on use of AI tools in real-world workflows. 3+ years of QA engineering experience, including at least 2+ years focused on automation. Proven hands-on experience using LLMs (e.g., GPT, Claude, Llama) as part of QA or engineering workflows. Strong programming skills in Python and experience with PyTest or similar frameworks. Solid understanding of REST APIs, client-server architecture, and distributed systems. Experience working with SQL databases such as PostgreSQL or ClickHouse. Hands-on experience integrating automated tests into CI/CD pipelines. Ability to work independently on complex systems and ambiguous business logic. Comfortable working in an EST timezone environment. Benefits Remote-first work environment 20 days of paid time off plus U.S. holidays Access to a modern AI-first technology stack with freedom to experiment High-autonomy,