As part of one or two cross-functional mobile product teams, you will own the quality of our Flutter apps, and change how we approach testing.
AI-driven QA is the differentiator in this role. Our QA team already uses AI for test generation, but we want to go much further. You will help invent this from scratch: autonomous exploration, smarter test orchestration, self-directed QA workflows, and QA systems that detect product risks before they reach users.
This is not a "write test cases and file tickets" role. You co-own product quality end-to-end, tell engineering teams where the gaps are, and build the systems and practices that let us ship with confidence. Faster, not slower.
You think about quality as something you design into the product and process, not a checklist you run before release.
Our Stack
- Flutter & TypeScript
- Appium, BrowserStack
- Testmo for test case management
- GCP, GitHub Actions, Datadog
- AI-assisted development with Cursor and agentic coding workflows
- Linear, Notion, Figma, Miro
Key Responsibilities
- Own quality across our mobile products end-to-end: test strategy, execution, and production monitoring
- Work embedded in one or two cross-functional product teams and shape quality practices with engineers, product, and design
- Find the gaps in our current testing approach and close them
- Grow and maintain our automated test suite (Appium / BrowserStack). Keep it fast, stable, trusted, and focused on critical user journeys
- Advise engineers on testing strategy and testability early, at the design stage, not after the build
- Push AI-driven QA beyond test generation: bring in autonomous exploratory testing, intelligent orchestration, and self-directed testing workflows
- Build QA feedback loops that are tightly integrated with development. Quality should be a real-time signal, not a gate at the end
- Keep test infrastructure healthy: less flakiness, faster runs, results the whole team can act on
- Use AI tools wherever they make you and the team more effective, and figure out where autonomous QA can reduce repetitive manual work while preserving human judgment where it matters