agentic world — and bring the teams along a journey to a more consistent, modern, AI-native software development lifecycle. Key ResponsibilitiesEngineering practice & SDLC maturity: raise the quality and consistency of software design, development, testing and delivery; improve route-to-live, release management, quality gates and CI/CD; reduce manual … developer experience; standardise and consolidate tooling where it creates clear value (including the move to GitHub as a strategic platform).AI adoption across the SDLC: drive practical adoption of AI-enabled engineering across development, testing, review, documentation and support, aligned to governance and measurable outcomes. Engineering metrics & insight: improve visibility ...