Mobile Quality Engineer, Lendable

• Hands-on experience with Maestro or Detox
• 2-3+ years in quality engineering or test automation, with a track record of keeping automated suites stable rather than letting them rot into a graveyard of quarantined tests
• Experience introducing AI-assisted testing practices (test generation, failure clustering, coverage analytics) with sensible controls around review and trust
• Strong TypeScript and JavaScript - not just writing test scripts, but building helpers, tooling, and debugging into the app when needed
• Experience shaping CI/CD pipelines for test reliability (GitHub Actions or similar), including flakiness reduction, parallelisation, artefact management, and runtime control
• Comfortable with mobile E2E automation, or strong E2E experience on another platform plus a credible plan for getting productive on mobile quickly
• Able to operate independently and drive improvements end-to-end (frameworks, CI, test data, reporting)

Desirable

• Our mobile app, Zable, is how most of our customers experience all of our products in one centralised space. It's written in React Native and TypeScript with a Kotlin backend, shipped to iOS and Android from a single codebase
• We are now looking to level up the quality engineering so that we can raise release cadence without losing sleep over regressions
• This is an automation-first role. You'll spend most of your time writing code - test frameworks, CI tooling, helpers, rather than executing test scripts by hand. You'll work alongside software engineers, product, and design, setting direction
• You'll also be working at the frontier of AI-assisted quality, using LLMs and AI tooling to speed up test authoring, triage failures, and surface coverage gaps, while applying the engineering judgement to keep tests trustworthy
• Define and evolve a pragmatic test pyramid for React Native - deciding where E2E is worth the weight and where logic belongs in faster layers (Jest, React Testing Library, component tests)
• Make deliberate calls about coverage, reliability, and speed trade-offs across the app
• Set the bar for what "ready to ship" looks like on mobile, and hold the line on it
• Create and maintain mobile E2E suites in Maestro, including the scaffolding around them - test data, device configuration, helpers, reporting
• Integrate suites into CI (GitHub Actions) so engineers get fast, trustworthy feedback on every PR and release candidates carry a signal people actually believe
• Drive flakiness down and time-to-diagnosis down. We treat a flaky test the same way we treat a broken test, and we expect root-cause work rather than retry-until-green
• Use AI tools day-to-day to accelerate test authoring, cluster failures, surface coverage insights, and propose fixes
• Decide where AI adds leverage and where a human eye is needed. A suite that looks comprehensive but isn't trustworthy is worse than a smaller one we rely on
• Help shape how the mobile team uses AI-assisted workflows more broadly - prompts, guardrails, review patterns
• Partner with product and engineering on shift-left quality: join specs early, push back on ambiguous acceptance criteria, and surface risk before code is written
• Close the loop on production issues using our observability stack (Datadog, Sentry, Grafana) - tying test coverage back to real customer impact
• Run targeted exploratory testing on high-risk releases when it's the right call

• Quick call with a Recruiter
• 15 minute cognitive test
• Hiring manager interview (30 minutes)
• Technical interview (90 minutes)
• Culture-add interview (60 minutes)