QA Engineer - Mobile(React Native)

**QA Engineer — Mobile (React Native)

Innovatily | Location: Bengaluru (or remote, per team norm) | Reports to: QA Lead / Engineering Manager
About the Role

Innovatily is hiring a manual QA Engineer to own quality for Innovatily apps built on React Native (iOS and Android). This role starts as hands-on manual testing and will grow into using AI-assisted testing tools (test case generation, triage copilots, self-healing automation) as those are introduced to the team — no prior AI tooling experience required, but technical curiosity is.

The single hardest part of this app to get right is location: continuous background GPS tracking while a ride is in progress, plus lighter single-point check-ins elsewhere in the flow. This JD is written around that reality — most of the role is normal mobile QA, but the location/background-tracking competency below is a hard requirement, not a nice-to-have.

**What You'll Own

Manual functional and exploratory testing across the iOS and Android apps (shared React Native codebase, platform-divergent native behavior)

End-to-end validation of continuous background location tracking during active rides — permission flows, tracking continuity, foreground service / background mode behavior, and recovery after signal loss or app backgrounding

Validation of single-point location check-ins (pickup confirmation, arrival detection, etc.)

Writing clear, reproducible bug reports (repro steps, expected vs. actual, severity, device/OS/build version, logs)

Building and maintaining a device/OS/OEM test matrix relevant to the Canadian market

Regression testing across app releases, with particular attention to permission and background-execution behavior, which changes materially between OS versions

Collaborating with engineering to distinguish app bugs from OS-level or OEM-level battery/background restrictions

Over time: working alongside AI-assisted QA tooling as it's introduced (test case generation, log triage, etc.) — training provided

**Must-Have Requirements

2+ years of manual QA experience on mobile apps (iOS and Android)

Direct prior experience testing an app with continuous background location tracking or a background service — rideshare, delivery/logistics, fleet management, or fitness/activity tracking apps all qualify. This is non-negotiable: it's the highest-risk, highest-impact bug class in this app, and it doesn't transfer well from testing apps that only use location as a single check-in.**

Working knowledge of iOS location permission tiers ("Always" vs. "While Using the App") and how backgrounding/throttling can affect tracking

Working knowledge of Android location permission tiers ("Allow all the time" vs. "While using the app"), foreground service requirements for background tracking, and permission auto-reset behavior on unused apps

Comfortable diagnosing whether a tracking failure is an app bug, a stock-OS restriction, or an OEM battery manager (e.g., Samsung's aggressive background app management) — or knows how to isolate this with engineering

Ability to write clear, technically precise bug reports that engineers can act on without back-and-forth

Comfortable with basic technical tooling: reading device logs (Xcode/Android Studio), using ADB commands, configuring simulator/emulator location mocking (GPX/KML routes)

Strongly Preferred

Testing experience specific to ride-share, delivery, or logistics apps

Familiarity with real-device testing constraints — why simulators/emulators cannot fully validate background tracking (GPS multipath, carrier handoff, real elapsed-time battery/OS behavior)

Exposure to cloud device farms (BrowserStack, Sauce Labs, Firebase Test Lab, AWS Device Farm) for cross-device regression coverage

Awareness of urban GPS challenges relevant to Canadian cities (indoor/underground signal loss, downtown multipath, highway carrier handoff between cities)

Basic scripting or config-file comfort (JSON, GPX editing) — a strong signal for how quickly they'll adapt to AI-assisted tooling later

Nice-to-Have (Not Required)

Prior use of AI-assisted QA tools (test case generators, triage copilots, self-healing test automation)

Automation scripting experience (Appium, Detox, XCUITest/Espresso) — not required for this role today, but a plus for growth into hybrid manual/automation work

Familiarity with PIPEDA or general data-consent/retention testing considerations for location data (we'll provide specifics; general awareness is the plus)