About the role

QA Manager leading end-to-end quality strategy across product releases at DataVisor. Driving automation and leveraging AI for efficiency in quality assurance processes.

Responsibilities

Own end-to-end quality strategy across product releases (planning, execution, release readiness).
Establish and continuously improve QA processes to reduce defects and release risk.
Lead strong defect management practices (triage, prioritization, root cause analysis, prevention).
Drive an automation-first approach to increase regression and critical-path coverage.
Apply AI tools to improve testing efficiency (e.g., test generation, regression optimization, defect clustering, RCA insights).
Define and track QA KPIs (defect leakage, escaped defects, automation coverage, flake rate, cycle time, release stability) and use data and dashboards to drive measurable improvements.
Lead, coach, and develop the QA team with clear goals and accountability.
Collaborate closely with Engineering, Product, DevOps, and Support.
Ensure QA is involved early in requirement and design discussions and clearly communicate quality risks, status, and release readiness.

10+ years of QA/testing experience, including 5+ years in a QA leadership role.
Proven experience building and scaling QA processes across multiple teams or products.
Strong knowledge of QA methodologies, test planning, defect lifecycle management, and release management.
Hands-on experience with test automation frameworks and CI/CD integration.
Demonstrated ownership mindset with strong execution focus, especially during tight release timelines.
Experience using AI tools or implementing AI-assisted QA workflows.
Strong experience defining QA metrics, building dashboards, and driving data-based decisions.
Excellent cross-functional communication and stakeholder management skills.