QA Engineer

Adventure is our Culture. Join a team that celebrates a lifestyle as bold as the terrain we love. At Backcountry, we are rooted in adventure, recognition, and wellbeing on and off the mountain. We spotlight employee stories, celebrate milestones, and offer exclusive outdoor perks. Whether you are at HQ, in a retail store, or remote, you will be part of a team that thrives on energy, exploration, and connection.

Reports to: Senior Retail Technology Architect

Location: Remote (US, Canada, or Costa Rica)

What You'll Do

Build AI-Accelerated Test Automation

• Build and maintain scalable automation suites using Playwright across web, API, and mobile, contributing to broader QA frameworks and release validation standards.
• Use AI coding assistants and agents (Claude Code, GitHub Copilot, Cursor, Playwright's planner/generator/healer agents) to generate test plans, test cases, page objects, and test data from requirements, Jira stories, and PR diffs.
• Review, validate, and harden every AI-generated test before it merges — you own the correctness of the suite regardless of what wrote the code.
• Drive down flaky tests and maintenance cost through resilient locator strategies, AI-assisted self-healing, and automated failure triage.
• Integrate automated quality gates into GitHub Actions CI/CD so every deploy is validated by the pipeline rather than by manual sign-off.
• Build and maintain functional, regression, API, and performance/load testing coverage using tools like Postman, JMeter, or k6.

Apply Testing Judgment Where It Matters

• Determine what should be automated, what can be delegated to AI, and what requires human testing — balancing coverage, risk, and release timelines.
• Perform focused exploratory testing on new features, UI/UX changes, and complex user flows to catch edge cases and usability issues that automation and AI miss.
• Turn every escaped defect into an automated regression check so the suite strengthens with each release.
• Partner with engineers to embed tests, API contract checks, and AI-assisted code review early in the SDLC to reduce downstream defect costs.
• Help define how to test AI-powered customer experiences (search, recommendations) where outputs are non-deterministic and need evaluation rubrics rather than exact assertions.
• Track and report quality metrics (automation coverage, defect escape rate, flake rate, test cycle time) to show where automation is paying off.

Contribute to a High-Performing Team