AI Enablement Lead

FDJ UNITED

AI Enablement Lead role at FDJ UNITED coaching teams to build AI solutions. Shaping standard processes for AI adoption in a regulated gaming environment.

Posted 7/4/2026full-timeLondon • 🇬🇧 United KingdomSeniorWebsite

About the role

Key responsibilities & impact

Design and deliver hands-on technical workshops for Tech teams — 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
Run structured AI opportunity audits within Tech teams: helping teams assess which use cases are quick wins they can deliver themselves, which need Architect-level guidance, and which are not worth pursuing
Create technical training content covering topics such as RAG (connecting AI to internal knowledge bases), 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
Ensure security, data governance, and compliance are embedded into every use case from the start — not treated as a gate at the end
Upskill teams on OBG’s Technology Release Process so they can self-serve: preparing documentation, completing governance checklists, and meeting production standards without needing hand-holding
Identify gaps in existing processes, documentation, or governance frameworks and flag them to the relevant owners
Coach Tech Innovators (domain experts building use cases) through the full lifecycle: from identifying where AI adds genuine value, through scoping and prototyping, to handing off complex builds for Architect-level support where needed

Requirements

What you’ll need

4–7 years in a hands-on technical role — data engineering, AI/ML engineering, solutions architecture, or DevOps
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

Benefits

Comp & perks

Health insurance
Flexible working hours
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Data EngineeringAI/ML EngineeringSolutions ArchitectureDevOpsLow-Code/No-Code AutomationREST APIsOAuth/SSO AuthenticationData Flow ManagementTechnical Training Content CreationDebugging and Troubleshooting

Soft Skills

CoachingCommunicationProblem-SolvingStakeholder PresentationProcess Improvement