Quality Engineering Lead, Norm AI

• 5+ years of experience in software engineering, QA, quality engineering, or test infrastructure roles
• Strong experience designing and executing test strategies for complex, evolving enterprise products
• Hands-on experience with end-to-end testing tools (e.g. Playwright, Cypress), and writing maintainable automated tests
• Comfort acting as both an individual contributor and quality process owner
• Experience with CI/CD systems and improving test visibility and observability
• High ownership mindset with strong collaboration and communication skills
• Ability to work cross-functionally with engineers, PMs, and designers to prioritize quality in the product lifecycle

Desirable

• We’re looking for our first Quality Engineering Lead to establish and scale our QA strategy at the forefront of AI-powered enterprise compliance software
• As our first dedicated quality hire, you’ll define and implement test processes, while partnering closely with engineering, product, and design to ensure our most complex and high-impact workflows are reliable and regression-resistant
• This is a hybrid role: part technical contributor, part process leader, and part future team building
• You’ll own the foundation of our quality efforts and help us evolve toward a scalable model that supports fast iteration without sacrificing stability
• Define and operationalize a pragmatic quality strategy that supports fast-moving, engineering-owned development
• Lead by example–writing, organizing, and maintaining regression test plans (manual and automated) for critical flows
• Partner with engineers to identify test gaps, reduce flakiness, and improve coverage across branching workflows
• Introduce and enforce lightweight release-readiness practices for high-risk changes
• Build tooling or partner with platform engineers to improve test infrastructure, data generation, and CI reliability
• Track and share key quality metrics (e.g. regression trends, test pass rates, flaky test triage)
• Own root cause analysis for regressions and help ensure long-term prevention
• Develop the roadmap to scale the QA function, including evaluating when and how to grow a team
• What success looks like after 30 days
• You’ve mapped out key risk areas in the product and identified priority test coverage gaps
• You’ve proposed a practical QA model that supports team-owned quality and minimizes regressions
• You’ve partnered with engineering leads to improve existing test coverage and reliability in CI
• You’ve begun organizing and documenting regression testing practices
• What success looks like after 90 days
• You’ve led structured regression testing cycles for high-risk workflows, with measurable impact
• You’ve introduced key process improvements that help engineers ship with more confidence
• You’ve established visibility into test failures, coverage gaps, and quality KPIs
• You’ve drafted a plan to scale the QA function, including staffing needs and tooling investments