QA Automation Engineer
Build and maintain automated test frameworks for fitness apps (web, iOS, Android) and integrate them into CI/CD, using AI tools to accelerate QA and tackle GPS/location edge cases.
- Compensation
- $100K–$130K / yr
- Location
- Remote
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Qa
- Posted
Skills
Must have
- 4+ years of software QA experience, including 2+ years in test automation
- Strong programming skills in Python, TypeScript/JavaScript, or Java
- Experience building or extending automation frameworks (Playwright/Cypress for web; Maestro/Appium/XCUITest/Espresso for mobile)
- Experience integrating automated tests into CI/CD pipelines (GitHub Actions, Jenkins, CircleCI, etc.)
- Automated API testing in code (beyond Postman collections)
- Experience using AI coding tools (Claude Code, Copilot, etc.) as a force multiplier
- Strong exploratory testing instincts and attention to detail
- Familiarity with bug tracking and test management tools (Jira, TestRail, etc.)
- Ability to work independently in ambiguous situations
Nice to have
- Experience testing GPS, mapping, or location-based applications
- Experience with performance/load testing (k6, Gatling, Locust, etc.)
- Experience with device farms or cloud testing platforms (BrowserStack, Firebase Test Lab, etc.)
Full description
ARE YOU READY TO TAKE YOUR CAREER TO NEW HEIGHTS? ARE YOU SEEKING A NEW CHALLENGE IN A DYNAMIC SECTOR?
This is a very exciting and highly innovative time here at Outside.
OUR TRUE NORTH:Outside Interactive, Inc., the premier hub for active lifestyle enthusiasts, offers best-in-class content and experiences to more than 70 million of the world’s most passionate outdoor, wellness, and endurance enthusiasts every month. We inspire a broad and diverse audience to do the activities they love with greater enjoyment, inspiration, and knowledge and are dedicated to making real change in the outdoor and fitness industries.
About the role
Come join the MapMyFitness team at Outside as a QA Automation Engineer. You will own the test automation strategy for MapMyRun, MapMyWalk, MapMyRide, and our other fitness tracking applications used by millions of athletes worldwide — designing the frameworks, building the coverage, and wiring it all into our CI/CD pipelines so the team can ship confidently and often.
We are a lean, AI-augmented engineering team. We use AI coding tools as a force multiplier across development and testing, and we’re looking for someone who is energized by that way of working — not someone who wants to run a large manual QA operation. You’ll work closely with engineers, product, design, and growth marketing, and you’ll tackle testing problems most QA roles never see: GPS route simulation, GPX replay, sensor and location mocking, and real-world edge cases across iOS, Android, and web.
MapMyFitness is more than a fitness tracking platform — it’s a community that empowers people to achieve their health and fitness goals through data-driven insights and connected experiences. Our North Star is to equip our users with the very best tools to track, analyze, and improve their active lifestyles.
What you will do
- Design, build, and maintain test automation frameworks for our web, iOS, and Android applications
- Integrate automated test suites into CI/CD pipelines so every merge is validated automatically, and own the health of those suites — flake triage, runtime, and reliability
- Build automated API test coverage for the services that power our apps
- Develop strategies for testing location-based features, including GPS simulation, GPX replay, and device sensor mocking
- Use AI tools to accelerate test authoring, maintenance, and analysis — and help define how AI fits into our QA workflows
- Perform targeted exploratory and regression testing on new features where human judgment adds the most value
- Document and track defects with clear reproduction steps and severity assessments
- Collaborate with engineers, product, and design to understand requirements, identify edge cases, and build testability into features from the start