Senior Quality Assurance Engineer

We're looking for a QA Engineer who tests sharply and thinks systematically about how to test smarter — someone equally comfortable running a rigorous manual regression pass and using AI tools to cut the busywork around it. This isn't a "QA is being replaced by AI" role. It's the opposite: verification by a skilled human is still the core of what we do, and we want someone who can free up more of their time for the testing that actually requires judgment.

You'll work across three product surfaces — a legacy web UI still on manual testing, a modern web UI with strong automation coverage, and a mobile app — with a live mandate to shrink the legacy manual-testing footprint through both migration and automation, not just add headcount to it.

• Own the full enhancement testing cycle — understand story/code impact, generate test cases, execute them, and report clear, evidence-backed results in Jira
• Run regression testing with judgment, not brute force — apply risk-based thinking to scope what actually needs retesting rather than defaulting to full manual sweeps
• Reproduce and triage support tickets efficiently, pulling context across Jira, Slack, and Confluence
• Perform sanity testing on production and flag issues fast, with visual-diff pre-checks as a first pass on UI changes
• Prioritize your own daily ticket queue by sprint, release date, and business priority
• Write bug reports and test case documentation that are consistent, reproducible, and useful to the next person who reads them
• Use AI tools (Claude and similar) as a working habit — for test case drafting from code diffs, comment/report templating, context-gathering across tools, and regression scoping — while knowing exactly where AI's output needs a human check before it's trusted
• Contribute to the legacy UI → modern UI transition by flagging which manual test flows are highest-value to automate next, and pairing with the automation engineer to migrate them

• 2+ years of hands-on manual QA experience, ideally across both legacy and modern web applications, plus mobile
• Strong test design fundamentals — can break down a story into edge cases and risk areas without hand-holding
• Comfort working directly with developers on acceptance criteria, code-diff context, and shift-left quality practices
• Practical experience with (or strong interest in) AI-assisted testing workflows — using LLMs for test case generation, evidence review, or ticket triage, and knowing their limits
• Familiarity with Jira, and ideally exposure to MCP-style tool integrations (Slack, Confluence, CI/CD pipelines) for faster context-gathering
• A skeptical, evidence-first mindset — you're excited about AI acceleration, but you validate before you trust, especially on regression scope and production sanity checks
• Bonus: exposure to automation frameworks (Playwright/Cypress) even if not your primary discipline — we value QA engineers who understand what "automatable" looks like, even if scripting isn't their day job