Senior QA Engineer, AI & Automation

CSC Generation is hiring a Senior QA Engineer for Backcountry to own AI-accelerated test automation and quality practices. The role builds and maintains automated testing frameworks and CI/CD quality gates, applies risk-based exploratory testing, and helps evaluate AI-powered customer experiences.

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 — 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 — 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

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
• 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
• Cypress or Selenium experience is a plus
• 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