
- Growth StageExpanding market presence
QA Engineer - Mobile(React Native)
- Remote (Everywhere) •
- |2 years of exp
- |Full Time
Onsite or remote
Not Available

About the job
**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)
About the company
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