Modoante
SwedenContractual TemporarySoftware Developers

AI Enablement Lead

FDJ UNITED | Stockholm, Stockholm County, Sweden | Salary not specified

Source: JobsPipe

Required Skills

api-designdata-sciencedata-engineeringdevops
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Role snapshot

Work model
On-site
Language
Not specified
Experience
Not specified
Posted
Posted 1 day ago
Application deadline
2026-10-20

What you'll do

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

#AIAgentDesign #RAGPipeline #PromptEngineering #AIWorkshopFacilitator #TechnicalAICoach #APIIntegration 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

#AIGovernance #DataGovernance #AICompliance #EnterpriseAISecurity #RegulatedIndustryAI 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

#MCPModelContextProtocol #RAGPipelineEngineer #EnterpriseAITransformation #AIAgentDeveloper #AIScaleEnablement 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

#GitHubCopilot #CodingAssistant #DeveloperProductivity #CursorAI #CodingAssistantAdoption 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.

#PromptEngineeringLead #n8nAutomation #LowCodeNoCode #DataEngineering #AIMLEngineering #SolutionsArchitecture #DevOps #APIIntegrationSpecialist 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 Stockholm #AI Enablement Program Lead In Stockholm #AI enablement in Stockholm #AI change lead in Stockholm #Experienced AI Engineer #iGamingAI #EnterpriseAI #AIAdoptionLead #TechLeadsweden #AIImplementationLead #AIEnablementLead

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