You've spent years mastering test automation — now imagine applying that expertise in a landscape where GenAI tools like Claude Code, Cursor, and OpenAI API aren't just buzzwords but daily instruments in your workflow. If you're the kind of engineer who sees quality not as a gate but as a competitive advantage, and you want to push the boundaries of what modern QA looks like, this is the role you've been waiting for.
What you will be doing
Designing and executing AI-augmented test strategies — leveraging GenAI tools (OpenAI API, Claude Code, Claude skills, Cursor) to accelerate test creation, expand coverage, and detect edge cases that manual approaches miss.
Building and maintaining robust Selenium-based automation frameworks across web applications, ensuring regression suites run reliably at scale.
Analyzing test data and production telemetry to identify failure patterns, prioritize defect fixes, and provide actionable quality metrics to engineering leadership.
Integrating automated tests into CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps)
so that every commit is validated before it reaches production.
Mentoring junior QA engineers on best practices in automation architecture, GenAI-assisted testing, and data-driven quality decisions.
What you will NOT be doing
Manual-only testing drudgery — you won't spend your days clicking through the same UI flows. Automation and AI handle the repetitive work; you focus on strategy and edge cases.
Working in a siloed QA department that only hears about features after they're built. You're embedded with engineering from design through deployment.
Maintaining legacy test suites no one cares about — we actively prune and refactor; every test earns its place in the pipeline.
Begging for infrastructure or tooling budget — GenAI tools, cloud resources, and up-to-date CI/CD platforms are already provisioned and encouraged.
Writing 50-page test plans that no one reads — documentation is lean, living, and tied directly t