AI Enablement Lead

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.
• 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

• 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.