Senior AI Test Automation Engineer

About the Role

This role sits at the intersection of full-stack engineering and applied AI, focusing on building intelligent quality systems for CarParts.com's eCommerce platform. AI is woven into how we write, run, and maintain tests:

• Every engineer uses AI coding assistants (Claude Code, Claude Cowork, GitHub Copilot, Cursor) as a daily multiplier
• Automate test writing with AI: agents draft Cypress and Playwright specs from requirements, user stories, and code diffs
• Automate test running with AI: intelligent test selection, automated failure triage, flaky-test detection, and self-healing locator strategies
• Our platform exposes MCP servers so LLM-powered tools can query test results, trigger suites, and act on real-time quality signals
• Treat prompt engineering and token economics as first-class engineering disciplines, reviewed in PRs alongside test code

Our Culture

• Hungry & Hardworking: We set ambitious goals, measure progress with clear metrics, and hold ourselves accountable to deliver results.
• Promote from Within: We reward top performers with opportunities for growth and advancement.
• Collaborative & In-Person: We believe the best ideas and fastest execution happen face-to-face.
• High Standards: We move quickly, pay attention to details, and dig deep—whether analyzing contracts, aggregating complex scenarios, or building data-driven presentations.
• No Passengers: We value grit, ownership, and the relentless pursuit of results.

Responsibilities

Build & Own Test Automation (50%)

• Design, develop, and maintain automated test suites in Cypress and Playwright for functional, regression, end-to-end, and cross-browser testing
• Build robust, scalable test frameworks: custom commands, fixtures, page objects, network interception, and mocking/stubbing for reliable execution
• Create test automation for microservice APIs, testing end-to-end or in isolation using mocks, stubs, and contract testing
• Cover SPA, PWA, responsive design, and MPA architectures across desktop and mobile browsers
• Integrate automated tests into CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI); monitor and maintain automated test execution
• Develop and execute performance and load testing scripts to identify bottlenecks, collaborating with performance engineers
• Perform targeted manual, exploratory, and UAT/production validation where automation is not yet the right tool

AI-Powered Test Writing & Running (30%)

• Automate test writing: build and refine AI agents and pipelines that generate Cypress and Playwright specs from requirements, user stories, acceptance criteria, and code diffs
• Automate test running: intelligent test selection based on change impact, automated failure triage with root-cause summaries, flaky-test detection and quarantine, and self-healing locators
• Write prompts, evaluation harnesses, and monitoring for AI-assisted testing workflows; treat them as code, version them, review them
• Evaluate AI-generated tests for correctness, coverage, and reliability; never accept output blindly
• Build shared tooling: CLI utilities, test data generators, and internal developer tools powered by AI
• Contribute to MCP servers and integrations that expose test infrastructure (suites, results, environments) to LLM-powered clients

Collaborate & Grow (20%)

• Work closely with developers to understand application architecture and expand test coverage; participate in design and code reviews to catch quality issues early
• Contribute to test planning and strategy discussions; define and execute test plans aligned with project timelines and goals
• Investigate and analyze defects, documenting and reporting issues with the detail teams need to resolve them quickly
• Mentor engineers on test automation and AI-assisted testing patterns; participate in internal trainings as an attendee, Subject Matter Expert, or trainer
• Adhere to department procedures, processes, and best practices: SDLC, Change Control Management, Agile ceremonies, and ticket management
• Stay current with AI/ML tooling, LLM advances, and testing ecosystem developments; bring what you learn back to the team

Requirements

Core Engineering & Test Automation

• Bachelor's degree in Computer Science, Software Engineering, or related field / equivalent experience
• 6+ years of software engineering experience with deep, hands-on test automation expertise
• Proficient in programming using JavaScript / Node.js; experience with TypeScript strongly preferred
• In-depth, hands-on expertise with Cypress and Playwright, including fixtures, network interception, parallelization, and cross-browser execution
• Proven experience with mocking and stubbing libraries and contract testing for APIs
• Proven experience creating test automation for microservice APIs, for end-to-end testing or testing API services in isolation using mocks
• Proven experience creating test automation for one or more application types: Single Page Application (SPA), Progressive Web App (PWA), responsive design, and Multi-Page Application (MPA)
• Proven experience using Git source control and continuous integration tools (Jenkins, GitHub Actions, GitLab CI)
• Solid understanding of software testing methodologies, test planning, and test case design
• Strong communication and collaboration skills to work effectively with cross-functional teams
• Excellent problem-solving and analytical skills to identify and troubleshoot issues
• Experienced working in Scrum teams; able to adapt to evolving project requirements and priorities
• Strong organizational and leadership skills
• Comfortable working on the command line

AI & Automation

• Hands-on experience using LLMs (OpenAI, Anthropic, or equivalent) to generate, refactor, and maintain test code
• Comfortable using AI coding assistants (GitHub Copilot, Claude Code, Claude Cowork, Cursor) daily to accelerate test development
• Able to write effective prompts for test generation, test data creation, refactoring, and documentation
• Demonstrated ability to build or extend AI-assisted testing workflows, such as:
  • Test generation from requirements, user stories, acceptance criteria, or code diffs
  • Intelligent test selection and prioritization based on change impact
  • Automated failure triage, root-cause summarization, and flaky-test detection
  • Self-healing locator and selector strategies
• Familiar with agentic concepts: tool-calling, structured output, multi-step task decomposition, and human-in-the-loop review checkpoints
• Understands foundational LLM concepts: tokens, temperature, context windows, embeddings, and RAG
• Can evaluate AI-generated tests and code for correctness, security, and coverage, not just accept output blindly

Nice to Have

• Experience with Selenium, Appium, Jest, or Puppeteer
• Proven experience testing applications built with frameworks like Express, Next.js, and React
• Experience designing or contributing to MCP servers or similar context-orchestration layers
• Experience with performance testing tools (k6, JMeter, Lighthouse)
• Experience with public cloud services (AWS, Azure, GCP)
• Experience with ecommerce/retail purchase journeys