Senior Quality Engineer, Lendable

• 5+ 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
• 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
• Native AI-assisted working style with receipts. You can describe projects where AI meaningfully changed how you worked - test authoring, failure triage, coverage analysis - and where you decided it wasn't the right tool
• Comfortable with mobile E2E automation, or strong E2E experience on another platform plus a credible plan for getting productive on mobile quickly. We use Maestro on React Native with TypeScript and Expo - familiarity helps, but we'll back someone strong to ramp
• Proactive, low-ego, and clear communicator, able to chase things down when blocked
• Able to operate independently and drive improvements end-to-end (frameworks, CI, test data, reporting)

Desirable

• We're hiring two Senior Quality Engineers to join our Mobile team at Lendable and help us ship our apps with confidence as we keep scaling
• Our mobile app, Zable, is how most of our customers experience Lendable, loans, credit cards, car finance, mobile plans, subscriptions, and new products in development all in one place. It's written in React Native and TypeScript with a Kotlin backend, shipped to iOS and Android from a single codebase, and it's already in good shape
• We are now looking to level up the quality engineering so 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
• Our tech stack
• Mobile: TypeScript, React Native, Expo, EAS, GraphQL, Relay, Jest, React Testing Library, Maestro
• Backend: Kotlin, PHP 8 (Symfony), AWS, Postgres, RabbitMQ, Docker, Kubernetes
• Tooling and observability: GitHub, GitHub Actions, Jira, Confluence, Datadog, Sentry, Grafana

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