QA Lead – AI Augmented

About the role

The QA Lead – AI Augmented defines and drives the quality strategy across the product lifecycle, embedding quality from requirements through production. The role combines quality engineering, strategic governance, risk‑based testing and AI‑enhanced practices while leading a team of QA professionals.

Key responsibilities

• Define and execute a QA strategy aligned with business objectives, product risk and delivery methodology.
• Establish testing approaches, quality gates, coverage targets, environments and release criteria.
• Apply risk‑based testing to prioritize effort and promote shift‑left, quality‑by‑design practices.
• Oversee functional, integration, regression, API, exploratory and end‑to‑end testing, and lead defect triage.
• Engage early in requirements and design discussions, challenge ambiguous specifications and identify risks before development.
• Leverage AI to identify quality gaps, generate insights, optimise regression scope and support quality dashboards.
• Lead, coach and develop QA engineers, define competency expectations and foster a culture of continuous learning.
• Communicate quality status, risks and release readiness to business, development, architecture and client stakeholders.

Required profile

• Bachelor’s degree in Computer Science, IT, Software Engineering or a related field.
• Extensive experience in software testing, quality assurance or quality engineering.
• Proven experience leading QA teams and managing complex testing initiatives.
• Experience working in Agile, Scrum and DevOps environments, with exposure to AI‑assisted testing tools.

Required skills

• Software testing and quality engineering methodologies.
• Risk‑based, shift‑left and quality‑by‑design testing approaches.
• API, functional, integration and end‑to‑end testing.
• Automation frameworks and tools.
• AI‑assisted testing tools and prompt‑engineering techniques.