We are looking for a Lead AI Engineer, specialising in AI Adoption and Governance with demonstrable hands-on practice in current AI engineering tooling with proven experience setting standards and guardrails across the Software Development Lifecycle (SDLC). Fluent in agentic ways of working including model selection, prompt / harness engineering, agent-tool integration (such as MCP), reusable skill and instruction packaging. The role pairs horizon scanning with practical delivery, spotting emerging capability maps and converting isolated experimentation into reusable, centralised adoption patterns. Initial emphasis on landscape setting, evaluation and standard design, shifting over time towards a forward deployed model. Strong stakeholder management is essential, internally across portfolios, professions and assurance functions, and externally with suppliers and technology providers. This is an influencing role rather than a mandating one, so success depends on evidence, brokering and consensus rather than formal authority over portfolio tooling decisions. This is a senior technical influence role rather than a conventional people-management position. The person should be capable of leading standards and adoption across multiple teams while remaining sufficiently hands-on to test approaches and work directly with delivery teams.Essential Hands-on practice with agentic AI engineering: building and running agent workflows, model selection, prompt / harness engineering, ..... full job details .....