- QA Driivz Mobile EV features such as charging, site discovery, payments, biometrics, history, profile, notifications etc. across Android (Kotlin), iOS (Swift), and the Driver Portal web flows.

- Author and maintain Testmo cases per the Driivz Testing Guideline; link every case to its Jira story; keep Epic-level QA aggregate estimates honest.

- Participate in PI-week QA scoping : name your test types, environments, risk rating, and cross-flavour scope on every committed Epic (per the QA sub-gate criteria ad).

- Review product specifications and identify test requirements before stories enter grooming.

- Validate AI-generated test artefacts - cases, scenarios, repro steps - and reject anything that doesn't survive critical review.

- Verify accessibility (TalkBack on Android, VoiceOver on iOS) and localisation (RTL, dates, currencies, numbers) on every shipped feature.

- Triage incoming bugs with clean repro, environment context, logs, and a justified severity.

- Partner with developers on risk-driven exploratory testing - the structured cases catch known unknowns; you find the unknown unknowns.

- Recommend improvements to product behaviour and user experience based on test findings.

What we're looking for :

- 5- 7 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 strong 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.

How we work :

- Quality is a gate, not an inspection. We catch issues at PI-week QA scoping, in spec review, and at story decomposition - not in the last sprint of the PI. By the time a story is in-sprint, its Testmo cases already exist.

- Risk decides depth. A high-risk Epic gets exploratory + deep regression + cross-flavour. A low-risk one gets the happy paths and the deltas. You make the call and defend it.

- You own a feature end-to-end across all three surfaces - Android, iOS, Driver Portal. We don't split testers by platform; the same person follows a feature from spec to ship. Context loss is the enemy.

- Pairing over silos. You pair with developers during spec review, exploratory sessions, and defect triage. PMs run their feature templates past you before PI commit. We're async-friendly otherwise.

- Claude is a peer, not a replacement. You delegate scaffolding to it, then verify with your own eyes. We share prompts and skill files the way other teams share code snippets.

- PIs and sprints. We work in PIs with regular sprints inside. QA scoping happens at the start of every PI - that's where you set the type-mix, environments, and risk rating for each Epic you'll own.

Bonus Points :

- Espresso, XCTest, KIF, Maestro, Detox, or Playwright familiarity - even just enough to read what the developers wrote.

- CI awareness : tests run there, flakiness is a bug, you don't accept "works on my machine" from yourself either.

- Performance instrumentation (Android Profiler, Instruments) when the feature has perf risk.

- Security and PII discipline - no PII in client logs, ever. (It's a Driivz Mobile rule.)

- Prior experience writing or contributing to a team Testing Guideline.

- Familiarity with cloud platforms (AWS, GCP, or similar) - useful for understanding the backend side of mobile feature tests.

- Knowledge of network protocols (HTTP, TCP) - useful when traces get hairy.

- Automation experience that you can bring into manual workflows when it pays off.

Tools you'll use :

- Testmo

- Jira

- Confluence

- Claude Code + the Driivz plugins

- Android Studio

- Xcode

- Charles / Proxyman

- Swagger

- Firebase - Teams.