AI QA Engineer

Own and enforce the gate criteria for User Acceptance Testing (UAT) on every release, with authority to block builds that do not meet quality standards.

Build and maintain automated regression test suites integrated in CI to catch regressions before UAT, including agent-based AI checks for workflow testing and triage at scale.

Run visual and workflow drift detection through screenshot regression with human review on all client-facing surfaces; provide quality reporting on defect escape, gate pass, and flaky-test rates to engineering leadership.

4+ years of experience in QA automation or software engineering in test owning automated suites.

Proficiency with modern end-to-end testing frameworks (e.g., Playwright, Cypress) and strong coding skills in Python and/or C#.

Experience building or running LLM-based testing agents and knowledge of their failure modes like nondeterminism and false passes.

Experience with AI-native working style using AI coding tools daily (e.g., Claude Code, Cursor).

Experience testing LLM-powered features and building evaluation mechanisms (evals).

Background in enterprise B2B or multi-tenant platforms with client-configurable workflows.

Experience working at companies transitioning from services-heavy to product-led, AI-enabled platform businesses.