Senior QA Engineer, AI & Automation

CSC Generation•San Jose, CA

5d•Remote

About The Position

Backcountry is hiring a Senior QA Engineer focused on AI and automation. This remote role builds and maintains scalable automated testing across web, API, and mobile, using Playwright and AI coding assistants to improve test generation, reliability, and release validation. The engineer is accountable for reviewing and hardening AI-generated tests, integrating quality gates into CI/CD, reducing flaky tests, and maintaining functional, regression, API, and performance/load testing coverage. The role applies risk-based judgment to decide what to automate, delegate to AI, or test manually. It includes exploratory testing, turning escaped defects into regression tests, embedding quality practices early in the SDLC, and defining evaluation approaches for non-deterministic AI-powered customer experiences. The engineer tracks quality metrics, collaborates across QA and engineering, improves processes, and supports and mentors QA engineers in automation and responsible AI-assisted testing. The position is remote in the US, Canada, or Costa Rica and reports to the Senior Retail Technology Architect. The interview process includes a mandatory in-person interview at the Salt Lake City office. The position cannot be filled by a B.C. resident.

Requirements

At least 5 years of experience in Quality Assurance and Testing, including at least 3 years building and maintaining test automation that runs in CI/CD.
Hands-on Playwright experience for web and API end-to-end automation.
Strong automation fundamentals, including designing, building, and maintaining scalable, reliable test suites and frameworks, and diagnosing and eliminating flaky tests.
Strong proficiency in TypeScript/JavaScript or Python; ability to write test code to production-code standards.
Day-to-day hands-on use of AI coding tools such as Claude Code, GitHub Copilot, or Cursor to write, refactor, and debug test code, with the discipline to validate and correct generated output.
Experience integrating automated tests into CI/CD pipelines, preferably GitHub Actions, including parallel execution, reporting, and quality gates.
Experience with functional, regression, API, and performance/load testing using Postman, JMeter, k6, or equivalent.
Strong exploratory testing skills and judgment to build risk-based strategies across automated, AI-assisted, and manual coverage.
SDLC and Agile experience, including defect lifecycle management using Jira and TestRail.
Ability to work under a steady release cadence and manage competing priorities with minimal supervision.
Must provide a valid LinkedIn profile URL in the application, or give a credible reason for not having one and provide alternative evidence of professional background.
Must be willing and able to attend a mandatory in-person interview with a team member before an offer.
Employment is contingent on a background check, including verification of prior employment dates.

Nice To Haves

Cypress or Selenium experience.
E-commerce QA automation experience, particularly in environments with frequent releases and CI/CD integration.
Experience building or adopting agentic testing workflows, such as 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 evaluating non-deterministic output.
Familiarity with BrowserStack or similar cloud device and browser grids.
Experience with observability tools such as Grafana or GCP-based infrastructure, including using production signals to prioritize test coverage.
Java experience.
Strong communication and collaboration skills, with the ability to work cross-functionally.

Responsibilities

Build and maintain scalable Playwright automation suites for web, API, and mobile, contributing to QA frameworks and release validation standards.
Use AI coding assistants and agents to generate test plans, test cases, page objects, and test data from requirements, Jira stories, and pull request diffs.
Review, validate, and harden AI-generated tests before they are merged, taking ownership of test-suite correctness.
Reduce flaky tests and maintenance costs through resilient locator strategies, self-healing approaches, and automated failure triage.
Integrate automated quality gates into GitHub Actions CI/CD so deployments are validated by pipelines.
Build and maintain functional, regression, API, and performance/load testing coverage.
Determine what should be automated, delegated to AI, or tested by people, balancing coverage, risk, and release timelines.
Perform exploratory testing on new features, UI/UX changes, and complex user flows.
Convert escaped defects into automated regression checks.
Partner with engineers to embed tests, API contract checks, and AI-assisted code review early in the SDLC.
Help define evaluation rubrics for non-deterministic AI-powered customer experiences such as search and recommendations.
Track and report quality metrics, including automation coverage, defect escape rate, flake rate, and test cycle time.
Collaborate with QA peers and engineering teams, sharing practices, knowledge, AI prompts, and workflows.
Provide input on engineering-wide quality practices and process improvements to reduce manual regression and UAT effort.
Support and mentor QA engineers in automation and responsible AI-assisted testing.