Transformation Delivery Lead; Hybrid; m​/f​/x​/d

Join us in shaping how a global Life & Health reinsurance leader bring AI to life ’ll help turn strategy into real business results by driving the end-to-end delivery of practical solutions that improve performance, support innovation, and make a meaningful difference across the business.

As our Delivery Lead, Business Enablement, you will sit at the intersection of business transformation, delivery execution, and technology enablement to bring AI use cases from idea to scaled operational adoption. You will partner with business leaders, product owners, and operational teams to develop delivery plans, drive execution, and embed solutions effectively into core business processes.

This role offers a unique opportunity to turn L&H Re’s AI ambition into measurable value, through disciplined delivery, strong stakeholder alignment, and practical adoption across global markets.

• Lead end-to-end AI delivery across a portfolio of use cases, taking initiatives from prioritisation and discovery through MVP, production rollout, and value realisation while ensuring alignment to business objectives, timelines, and quality expectations
• Translate business needs into executable delivery plans by shaping scope, defining user stories and acceptance criteria, sequencing work into deliverable increments, and maintaining a clear backlog that balances value, feasibility, and risk
• Coordinate cross‑functional delivery teams across business, data, engineering, architecture, security, risk, and operations to ensure AI solutions are integrated effectively into target processes and are ready for scaled adoption
• Ensure production readiness and responsible delivery by partnering with technical teams to address testing, controls, model lifecycle considerations, data quality, security, supportability, and regulatory expectations relevant to AI‑enabled solutions
• Drive business adoption and measurable outcomes by supporting user testing, rollout planning, training, feedback loops, and post‑launch optimisation, with a strong focus on realised benefits, operational improvement, and sustainable ways of working
• Build delivery capability and delivery standards by embedding reusable playbooks, agile delivery disciplines, documentation standards, and lessons learned that improve execution quality across future AI initiatives

• 5+ years of experience in delivery leadership, product delivery, programme management, business analysis, or a similar role, ideally gained in insurance, reinsurance, financial services, consulting, or another regulated environment
• Strong understanding of AI and digital delivery life cycles, including how to take use cases from discovery and MVP through implementation, rollout, adoption, and ongoing optimisation in an enterprise setting
• Proven ability to turn ambiguous business problems into structured delivery plans, clear requirements, prioritised backlogs, realistic milestones, and measurable success criteria
• Strong stakeholder management, communication, and facilitation skills, with the ability to work credibly across senior business leaders, product owners, architects, engineers, and operational teams
• Proven track record of managing risks, dependencies, and delivery trade‑offs in complex cross‑functional programmes, while maintaining momentum, transparency, and high‑quality execution

• Experience in Life & Health insurance or reinsurance, with a practical understanding of core value chain activities and how AI‑enabled solutions can improve workflow efficiency, decision quality, and client outcomes
• Experience delivering AI, analytics, automation, or digital transformation initiatives, including coordination of pilots, MVPs, and scaled rollout in partnership with technical and business teams
• Familiarity with agile delivery methods, product ownership practices, and delivery tooling such as Jira, Azure Dev Ops, or equivalent platforms used to manage backlog, progress, and dependencies
• Familiarity with data governance, model risk, privacy, security, and regulatory considerations relevant to AI delivery…