The core responsibilities for the job include the following:

Test Automation Infrastructure:

- Playwright regression suites: build and grow suites across search, company and people views, lists, signals, credits, sign-up, and CRM flows; own page object patterns, parallelism, and retries.
- Synthetic monitoring: run Checkly production monitoring; configure alerts and SLOs; own the health of journeys that matter.
- CI/CD quality gates: build gates against preview and staging deployments; own gate configuration and failure analysis.
- Test data management: manage and maintain test data; ensure data isolation and repeatability.

Quality through design:

- Flaky test debugging: find and fix the root cause of flaky tests; own test reliability and suite speed. API and integration testing: test APIs (REST, auth, and role-based access control); test integrations end-to-end with HubSpot, Salesforce, Dynamics, Pipedrive, and our Chrome extension.
- Test design: turn rough testing notes into clear, structured test cases; own test strategy and coverage decisions; AI-assisted testing.
- Agentic and LLM-assisted tests: lead the move to AI-assisted testing using frameworks like Browser Use, Stagehand, or Playwright MCP; experiment with agentic and natural-language browser tests.
- AI-generated test cases: work with LLM-generated test cases from specs; use Claude Code or Cursor to write, maintain, and review test specs.
- Quality reporting: publish regression reports that engineers and product managers understand; speak up early and clearly.

Requirements:

- 5+ years of test automation in Playwright: you've built and maintained production Playwright suites in TypeScript or JavaScript; you know the framework inside out.
- Solid test design: page objects, test strategy, parallelism,



retries; you know how to find and fix the root cause of flaky tests, not just re-run them.
- API testing and CI/CD: REST API testing, auth and access control testing, integrating suites into CI/CD (GitHub Actions or similar), and building quality gates.
- Hands-on AI in testing: you've generated, run, maintained, or triaged AI-assisted tests.
- You can explain where it worked and where it didn't.
- You use AI coding assistants (Claude Code, Cursor) every day and review their output critically.
- Very good communication: explicit written bug reports and test reports; confidence pushing back on a release when the risk is real; comfort working async with a team in Australia.
- Product mindset: you think like a customer; you prioritize by risk, not by coverage numbers. You care about what matters to users, not just coverage metrics.
- You live and breathe AI tools.
- You use AI daily for test spec writing, test generation, debugging test failures, and test maintenance as your default way of working, not a productivity experiment. In 2026, this is how test automation moves fast, and you need to already be doing it.
- Highly Valued Synthetic Monitoring: Checkly or similar production monitoring, alert configuration, and SLO thinking; Chrome extensions or complex integrations: hands-on experience testing browser extensions or thick CRM integrations.
- Agentic testing frameworks: Browser Use, Stagehand, Playwright MCP, or similar; experience experimenting with agentic approaches. Performance and load testing: k6 or similar; understanding of performance constraints in web testing.
- Visual regression testing: tools and patterns for visual regression; SQL and test data: Postgres/Supabase knowledge for managing and seeding B2B test data; SaaS or data products: experience in B2B or data-heavy products where quality and integration complexity matter

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📌 Senior QA Automation Engineer (Melbourne)
🏢 Firmable
📍 Melbourne