What we're looking for

- 5-10 years of hands-on mobile QA on shipped Android + iOS production apps.

- Strong native-platform awareness: Android API 24 34+ fragmentation, iOS 15+ background-refresh non-determinism, deep-link routing, push notifications, offline behaviour, biometric auth, lifecycle edge cases.

- Driver Portal / web QA experience or a robust willingness to span. We don't split testers by platform; you cover the full driver journey.

- Multi-tenant / multi-flavour parametric testing. You don't write a case four times; you write it once and parametrise.

- Accessibility: TalkBack, VoiceOver, contrast ratios, touch-target sizing, keyboard navigation.

- Localisation: RTL handling, locale-dependent formatting.

- Risk-based test depth you know when 30 cases is right and when 8 plus exploratory is right.

- Network conditioning (Charles or Proxyman); real-device labs and cloud labs (Firebase Test Lab, BrowserStack, or equivalent).

- Comfortable testing RESTful APIs and reading mobile network traces both client- and server-side awareness.

- Bug triage with clean repro steps, environment, logs, severity, blast radius. Strong analytical and root-cause skills under pressure.

- Excellent English communication, both verbal and written.

- Self-starter, quick learner, comfortable working independently across cross-functional teams.

AI-era skills we're hiring for (the differentiator)

- Fluent with Claude Code as a daily tool. Skills, agents, plugins,



MCP servers — you use them to accelerate test design, generate edge cases from a spec, and pressure-test acceptance criteria.

- Authoring Testmo cases from a spec with AI scaffolding, then editing with judgement. You know that AI-generated cases are starting points, not deliverables.

- You read AI-generated spec analysis and feedback the Testing Guideline section that applies — shaping the downstream test-case generation before it runs.

- You spot AI failure modes — hallucinated steps, false coverage, plausible-but-wrong assertions, over-generic cases. You treat AI output like a junior engineer's PR: verify before merge.

- You know when NOT to use AI — security-sensitive flows, brand-critical UX moments, exploratory sessions where serendipity is the value, anything with regulatory exposure.

- You'll test code that AI developer agents authored and AI PR-reviewer agents approved — you know how these agents fail, which seams they get wrong, and where regression risk concentrates after AI-authored changes.

- You communicate in chain vocabulary — gates, contracts, state-transitions, Epics, stories. You think in graded handoffs, not just features.

The bar isn't uses AI tools. The bar is judges AI output well.

Tools you'll use

Testmo • Jira • Confluence • Claude Code + the plugins • Android Studio • Xcode • Charles / Proxyman • Swagger • Firebase • Teams.

📌 Senior Mobile QA Engineer (Bengaluru)
🏢 Gilbarco Veeder-Root
📍 Bengaluru