- Lead and manage 27 staff across Discovery and Delivery functions, driving performance, accountability, resource planning, team development and continuous improvement.
- Oversee the full product lifecycle, from strategic planning, AI-enabled discovery and requirements engineering through solution design, development, testing and production release.
- Drive generative AI adoption across business analysis, requirements, solution shaping, backlog refinement and quarterly planning.
- Lead the adoption of AI-assisted software development practices across the SDLC.
- Champion AI-powered testing and quality engineering using Claude, Zephyr and Playwright, reducing manual effort and advancing automated testing.
- Establish and mature delivery frameworks, Definition of Ready, Definition of Done, quality gates and engineering standards.
- Shape AI transformation strategy, governance frameworks and scalable operating models across Discovery, Engineering and Delivery.
- Promote secure, ethical and compliant AI adoption incorporating data protection, human oversight and risk management.
- Lead portfolio governance, stakeholder engagement, delivery reporting, risk management and Change Advisory Board (CAB) processes.
AI transformationAI-assisted SDLCQA automationResponsible AIAgile operating model