AI Enablement Lead

About the Company FDJ UNITED operates in igaming under strict regulatory oversight. Security and governance are not optional extras here — they are the baseline. About the Role FDJ United is hiring an AI Enablement Lead to drive enterprise AI transformation across our Tech function of 1,000+ people, based in South Wimbledon, London. This is a rare opportunity for a Technical AI Coach or AI Adoption Lead who has spent years building production systems and now wants to make entire engineering organisations better at doing the same. This is not a lecture-based training role. As our AI Enablement Lead, you will be hands-on — coaching engineers, running live workshops, and embedding governance and security into every AI use case from day one. You will define what good looks like for enterprise AI enablement in a regulated iGaming environment. If you are an experienced AI Implementation Lead or AI Transformation Lead who thrives in fast-paced, high-stakes environments and has a strong instinct for teaching rather than doing, this role is for you. Responsibilities Technical Coaching & Upskilling

• Design and deliver hands-on technical workshops for Tech teams as a Technical AI Coach — the kind where participants build and ship working AI agents themselves, not watch someone else do it
• Coach engineers and domain experts through identifying real use cases in their function, scoping them rigorously, and building their first working solutions on KAIT — your success is measured by what they can do independently
• Run structured AI opportunity audits within Tech teams: helping teams assess which use cases are quick wins, which need Architect-level guidance, and which are not worth pursuing
• Create technical training content covering RAG pipelines, AI agent design, prompt engineering, and API integration — written for a Tech audience, grounded in real OBG scenarios
• Provide floor support during workshop sessions, including live debugging and troubleshooting — guiding participants through solving problems, not solving for them Governance, Security & Process
• As an Enterprise AI Enablement specialist, ensure security, data governance, and compliance are embedded into every use case from the start — not treated as a gate at the end
• Train teams to think about data classification, human oversight, and audit requirements as part of their design process — core to any regulated industry AI role
• Upskill teams on OBG's Technology Release Process so they can self-serve: preparing documentation, completing governance checklists, and meeting production standards
• Identify gaps in existing processes, documentation, or governance frameworks and work with A&I and platform teams to close those gaps through training and upskilling Use Case Pipeline & Enablement at Scale
• Coach Tech Innovators through the full lifecycle as an AI Adoption Lead: from identifying where AI adds genuine value, through scoping and prototyping, to handing off complex builds for Architect-level support
• For high-complexity use cases (multi-system integrations, MCP connectors, RAG pipelines), guide and upskill teams responsible for delivery — your role as an AI Transformation Lead is to transfer capability, not accumulate it
• Assess incoming use cases and route them correctly: straightforward AI agent builds, strategic projects needing deeper support, and cases that belong in data science or other disciplines Developer Productivity (Secondary — ~20% of Time)
• Deliver structured workshops and a best-practice guide for coding assistant adoption (e.g. GitHub Copilot, Cursor) across engineering teams
• Engineering team leads retain accountability for sustained adoption in their teams
• This is a secondary workstream — deprioritised if the main AI enablement pipeline requires full capacity Qualifications Essential
• 4–7 years in a hands-on technical role — data engineering, AI/ML engineering, solutions architecture, or DevOps — with a subsequent move into enablement, consultancy, or internal transformation.
• Proven experience coaching technical teams to build and deploy AI agents or RAG pipelines in production — not just building them yourself.
• Hands-on with at least one low-code/no-code automation platform (e.g. n8n) — enough to credibly train others.
• Strong prompt engineering knowledge: system-level prompts, structured output, chain-of-thought, evaluation techniques — and the ability to teach these to others.
• Solid understanding of enterprise integration patterns: REST APIs, OAuth/SSO authentication, rate limiting, data flow between systems.
• Demonstrable commitment to governance and process: you embed security, data classification, and compliance into how teams work, and you flag gaps when processes are missing or unclear.
• Track record of delivering technical workshops where participants built tangible solutions themselves — not lecture-based training.
• Ability to translate complex technical concepts clearly for non-technical audiences and present credibly to senior stakeholders. Highly Desirable
• Experience in a regulated industry: igaming, fintech, or financial services.
• Hands-on n8n experience for production workflow automation.
• Familiarity with MCP (Model Context Protocol) or similar frameworks for connecting AI agents to enterprise systems.
• Experience with LLM providers (OpenAI, Anthropic) for inference and evaluation.
• Working knowledge of vector databases, embedding models, and semantic search.
• Experience with coding assistants (GitHub Copilot, Cursor) in a developer productivity context.
• Multi-site or international delivery experience. AI Adoption Facilitator in London AI Enablement Program Lead In London AI enablement in London AI change lead in London Experienced AI Engineer iGamingAI EnterpriseAI AIAdoptionLead TechLeadLondon AIImplementationLead AIEnablementLead