Senior Quality Engineer (Mobile)

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 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.

What you'll be doing

Own the mobile test strategy:

• 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.

Build reliable E2E automation:

• 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.

Bring AI into the SDLC:

• 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.

Prevent defects, not just catch them:

• 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.

What we're looking for

Essential:

• 6+ 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:

• Hands-on with Maestro or Detox.
• Hands-on experience testing React Native apps.
• Mobile performance and reliability work (crash reporting, startup time, memory and battery awareness).
• API and contract testing experience, with a point of view on test data and environment strategy.

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.