Description We’re looking for a QA Engineering Lead to raise the bar for quality across our web, mobile, and desktop products. This is a hands-on, high-impact role for someone who can build scalable test automation, turn quality into a measurable engineering discipline, and help teams ship with confidence. You’ll work across teams, influence engineering decisions, and build systems that make quality scale beyond the QA team. Key responsibilities You’ll own the quality engineering strategy across our web, mobile, and desktop products. Your goal is not to write more tests, but to build a system where effective tests are easy to create, trusted, and strong enough to gate releases. You’ll work across engineering teams to: Build and evolve automation platforms, frameworks, and standards Establish quality metrics and use them to drive engineering decisions Improve test effectiveness, reliability, and feedback speed Coach QA/SDET engineers and developers across teams without formal authority Build tooling that enables developers — and AI coding agents — to create and maintain effective tests Partner with engineering leadership on release risk and quality trade-offs Requirements What we're looking for: Demonstrated impact: You have taken a team or organization from “tests exist but protect nothing” to automated testing that reliably gates releases — and can show the before/after in numbers: coverage, escaped defects, release cadence, flaky-test rate, or similar. Cross-platform automation: You have production experience across web, mobile, and desktop , with hands-on depth in at least two and architecture/review-level experience in the third. Web: Playwright or equivalent at scale; maintainable architecture, parallelization, and a systematic approach to flaky tests Mobile: Maestro, Detox, Appium, or equivalent; release trains, staged rollouts, and reliable device/emulator CI Desktop: native applications across Windows/macOS/Linux; visual regression; C++/Qt is a plus Specific tools are less important than strong engineering fundamentals and the ability to choose the right approach. Quality & CI/CD: You treat quality as an engineering metric. You’ve established baselines, tracked meaningful trends, and validated that tests actually detect defects — through mutation testing or equivalent practices. You have operated large automated suites as real CI/CD gates, including required checks, branch protection, reliability, and feedback-speed trade-offs. AI-assisted engineering: You have hands-on experience with AI-assisted coding and test generation (e.g. Claude Code, Cursor, or similar) and a clear point of view on when generated tests provide real protection versus simply inflating coverage. Leadership: You grow engineers without needing line authority. You can point to people who became stronger automation engineers through your coaching. You can defend quality decisions with data and trade-offs, including knowing when to stop a release and when the risk is acceptable. English: Upper-Intermediate
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