They leverage automation platforms, AI-enabled quality capabilities, observability data, quality intelligence, and modern engineering practices to continuously assess product health, identify risk, drive improvements, and influence better decisions across product, development, and business teams. They do not manage people but are expected to manage complex quality initiatives, influence technical and business decisions, guide quality strategy, and drive measurable improvements in product outcomes through technology, automation, data, and expertise.