Senior QA Engineer, AI & Automation

CSC Generation•San Jose, CA

10d•Remote

About The Position

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)

Requirements

5+ years of experience in Quality Assurance and Testing, including 3+ years building and maintaining test automation that runs in CI/CD.
Proven, hands-on experience with Playwright for web and API E2E automation; Cypress or Selenium experience is a plus.
Strong automation fundamentals: ability to design, build, and maintain scalable, reliable test suites and frameworks, and to diagnose and eliminate flaky tests.
Strong proficiency in TypeScript/JavaScript or Python (Java a plus); you write test code to the same standard as production code.
Hands-on, day-to-day use of AI coding tools (Claude Code, GitHub Copilot, or Cursor) to write, refactor, and debug test code, with the discipline to validate and correct AI-generated output.
Experience integrating automated tests into CI/CD pipelines (GitHub Actions preferred), including parallel execution, reporting, and quality gates.
Solid experience with functional, regression, API, and performance/load testing (Postman, JMeter, k6, or equivalent).
Strong exploratory testing skills and the judgment to build risk-based test strategies across automated, AI-assisted, and manual coverage.
Demonstrated SDLC and Agile experience with defect lifecycle management using Jira and TestRail.
Ability to operate effectively under a steady release cadence and manage competing priorities with minimal supervision.
Part of our interview process is a mandatory in-person interview with someone on our team prior to an offer. Candidates that are unwilling or unable to meet for an in-person interview will be removed from consideration immediately.
Due to a high volume of fraudulent applications, you must share a valid LinkedIn profile URL in the application questions below to be considered. If you do not have a LinkedIn profile, you must provide a credible reason in that field and supply alternative evidence of your professional background to verify your identity.

Nice To Haves

E-commerce QA automation experience, particularly in environments shipping frequently with CI/CD integration.
Experience building or adopting agentic testing workflows (AI test generation, self-healing tests, MCP-connected tools, or LLM-based failure triage).
Experience testing AI/ML-powered features such as search, recommendations, or LLM-generated content, including evaluation of non-deterministic output.
Familiarity with BrowserStack or similar cloud device and browser grids.
Experience with observability tooling like Grafana or GCP-based infrastructure, including using production signals to prioritize test coverage.
Strong communication and collaboration skills, with the ability to work cross-functionally.

Responsibilities

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 â€” 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.
Determine what should be automated, what can be delegated to AI, and what requires human testing â€” 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.
Collaborate with QA peers and engineering teams, sharing knowledge, best practices, and the AI prompts and workflows that work.
Provide input on quality practices and process improvements across the engineering org, focusing on reducing manual regression and UAT effort.
Support and mentor QA engineers on automation and responsible AI-assisted testing, fostering a culture of quality ownership.