AI Enablement Lead
FDJ UNITED is looking for an AI Enablement Lead to make teams self-sufficient in building and deploying AI solutions. This is a coaching and upskilling role with genuine technical depth, requiring the ability to train others on how production AI systems work.
The role involves working across OBG’s Technology function to drive adoption of the internal AI platform, KAIT, from early-adopter usage into mainstream practice. This includes running workshops where participants build working solutions, coaching teams through scoping and delivering their own AI use cases, and ensuring security, data governance, and release processes are embedded from the start.
The AI Enablement Lead will upskill teams so they move from occasional use to confident, governed, daily AI-assisted working. Where gaps in process, documentation, or governance are spotted, the individual will flag them and work with relevant owners to close them.
- Design and deliver hands-on technical workshops for Tech teams where participants build and ship working AI agents.
- 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 to help teams assess which use cases are quick wins, 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.
- Provide floor support during workshop sessions, including live debugging and troubleshooting, guiding participants through solving problems.
- Ensure security, data governance, and compliance are embedded into every use case from the start.
- 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 flag them to the relevant owners.
- Coach Tech Innovators through the full lifecycle of AI use cases, 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 the teams responsible for delivery rather than owning the build.
- Assess incoming use cases and route them correctly: straightforward agent builds that teams can own, strategic projects needing deeper technical support, and cases that belong in data science or other disciplines rather than KAIT.
- Deliver structured workshops and a best-practice guide for coding assistant adoption (e.g. GitHub Copilot, Cursor) across engineering teams.
- 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 (required)
- Proven experience coaching technical teams to build and deploy AI agents or RAG pipelines in production (required)
- Hands-on with at least one low-code/no-code automation platform (e.g. n8n) - enough to credibly train others (required)
- Strong prompt engineering knowledge: system-level prompts, structured output, chain-of-thought, evaluation techniques - and the ability to teach these to others (required)
- Solid understanding of enterprise integration patterns: REST APIs, OAuth/SSO authentication, rate limiting, data flow between systems (required)
- Demonstrable commitment to governance and process: embedding security, data classification, and compliance into how teams work, and flagging gaps when processes are missing or unclear (required)
- Track record of delivering technical workshops where participants built tangible solutions themselves (required)
- Ability to translate complex technical concepts clearly for non-technical audiences and present credibly to senior stakeholders (required)
- Experience in a regulated industry: igaming, fintech, or financial services (preferred)
- Hands-on n8n experience for production workflow automation (preferred)
- Familiarity with MCP (Model Context Protocol) or similar frameworks for connecting AI agents to enterprise systems (preferred)
- Experience with LLM providers (OpenAI, Anthropic) for inference and evaluation (preferred)
- Working knowledge of vector databases, embedding models, and semantic search (preferred)
- Experience with coding assistants (GitHub Copilot, Cursor) in a developer productivity context (preferred)
- Multi-site or international delivery experience (preferred)
FDJ United is one of Europe's largest gaming and betting groups, formed after French lottery operator La Française des Jeux (FDJ) acquired Kindred Group - the company behind Unibet - in 2024 and rebranded the enlarged group in 2025. Headquartered in Boulogne-Billancourt, France, it operates lottery, online sports betting, casino and poker across multiple European markets and Australia. Its portfolio includes well-known online brands such as Unibet, 32Red and Maria Casino, alongside FDJ's French lottery and retail network. The group is listed on the Euronext Paris exchange.