AI Enablement Lead

Kindred (London) Limited; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

FDJ UNITED is seeking an AI Enablement Lead to coach Tech teams in building and deploying AI solutions, focusing on self‑sufficiency, governance, and scalable workflows. The role requires hands‑on technical depth and strong teaching ability to uplift a large tech organization.

You will design workshops, run AI opportunity audits, and create training content on RAG, AI agents, and API integration. Experience with low‑code platforms and security governance is essential.

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.
• Hands‑on with at least one low‑code/no‑code automation platform (e.g., n8n).
• Strong prompt engineering knowledge and ability to teach it.
• Solid understanding of enterprise integration patterns: REST APIs, OAuth/SSO, rate limiting, data flow.
• Commitment to governance: embedding security, data classification, compliance, and flagging gaps.
• Track record of delivering technical workshops where participants built tangible solutions.
• Ability to translate complex technical concepts for non‑technical audiences and present to senior stakeholders.

Responsibilities

• Design and deliver hands‑on technical workshops for Tech teams – participants build and ship working AI agents themselves.
• Coach engineers and domain experts through identifying real use cases, scoping them rigorously, and building their first working solutions on KAIT.
• Run structured AI opportunity audits within Tech teams to assess quick‑win candidates, needs for architect‑level guidance, and non‑worth‑pursuing cases.
• Create technical training content on RAG, AI agent design, prompt engineering, and API integration for a Tech audience.
• Provide floor support during workshops, including live debugging and troubleshooting.
• Governance, Security & Process: Ensure security, data governance, and compliance are embedded from the start.
• Upskill teams on data classification, human oversight, and audit requirements.
• Train teams on OBG’s Technology Release Process.
• Identify gaps in processes, documentation, or governance frameworks and work with owners to close them.
• Use Case Pipeline & Enablement at Scale: Coach Tech Innovators through the full lifecycle of AI use cases.
• Guide and upskill teams for high‑complexity use cases rather than owning the build.
• Assess incoming use cases and route them: straightforward builds, strategic projects, or handoff to data science.
• Developer Productivity (Secondary — ~20% of Time): Deliver workshops and best‑practice guide for coding assistant adoption (GitHub Copilot, Cursor).

Skills

AI/ML engineering

data engineering

solutions architecture

DevOps

coaching

prompt engineering

REST APIs

OAuth/SSO

governance

data governance

security

workshops

stakeholder communication

Tools

n8n

GitHub Copilot

Cursor

Job description

At FDJ UNITED, we don’t just follow the game, we reinvent it. FDJ UNITED is one of Europe’s leading betting and gaming operators, with a vast portfolio of iconic brands and a reputation for technological excellence. With more than 5,000 employees and a presence in around fifteen regulated markets, the Group offers a diversified, responsible range of games, both under exclusive rights and open to competition. We set new standards, proving that entertainment and safety can go hand in hand. Here, you’ll work alongside a team of passionate individuals dedicated to delivering the best and safest entertaining experiences for our customers every day. We’re looking for bold people who are eager to succeed and ready to level‑up the game. If you thrive on innovation, embrace challenges, and want to make a real impact at all levels, FDJ UNITED is your playing field.

About the Role

We are looking for an AI Enablement Lead who can make teams self‑sufficient in building and deploying AI solutions — not someone who builds for them. This is a coaching and upskilling role with genuine technical depth.

Key Responsibilities

• Design and deliver hands‑on technical workshops for Tech teams – participants build and ship working AI agents themselves.
• Coach engineers and domain experts through identifying real use cases, scoping them rigorously, and building their first working solutions on KAIT. Success is measured by independent use.
• Run structured AI opportunity audits within Tech teams to assess quick‑win candidates, needs for architect‑level guidance, and non‑worth‑pursuing cases.
• Create technical training content on RAG, AI agent design, prompt engineering, and API integration for a Tech audience.
• Provide floor support during workshops, including live debugging and troubleshooting.
• Governance, Security & Process
  • Ensure security, data governance, and compliance are embedded from the start.
  • Upskill teams on data classification, human oversight, and audit requirements.
  • Train teams on OBG’s Technology Release Process.
  • Identify gaps in processes, documentation, or governance frameworks and work with owners to close them.
• Use Case Pipeline & Enablement at Scale
  • Coach Tech Innovators through the full lifecycle of AI use cases.
  • Guide and upskill teams for high‑complexity use cases rather than owning the build.
  • Assess incoming use cases and route them: straightforward builds, strategic projects, or handoff to data science.
• Developer Productivity (Secondary — ~20% of Time)
  • Deliver workshops and best‑practice guide for coding assistant adoption (GitHub Copilot, Cursor).
  • Prioritise if the main AI enablement pipeline requires full capacity.

Required Skills & 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.
• Hands‑on with at least one low‑code/no‑code automation platform (e.g., n8n).
• Strong prompt engineering knowledge and ability to teach it.
• Solid understanding of enterprise integration patterns: REST APIs, OAuth/SSO, rate limiting, data flow.
• Commitment to governance: embedding security, data classification, compliance, and flagging gaps.
• Track record of delivering technical workshops where participants built tangible solutions.
• Ability to translate complex technical concepts for non‑technical audiences and present 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.
• 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.

What We’re Looking For

Strong candidates have spent several years building production systems and then moved into a role focused on enabling others. They are not a career trainer who just picked up AI recently, nor a pure engineer who never coached a team. They understand multi‑step automated workflows end‑to‑end and instinctively teach teams to build them. They hold strong opinions about governance and process, embed them from the start, and flag gaps. They are comfortable with ambiguity, can challenge senior stakeholders, and help teams ship useful solutions rather than chase perfection.

Why This Role

• Direct impact as the single point of contact for AI capability uplift across a Tech function of 1,000+ people.
• Broad exposure: coach managers, review solution designs, run workshops, and flag process gaps.
• Shape the standard: define processes, governance habits, and quality standards for AI adoption.
• Regulated, high‑stakes environment: security and governance are baseline requirements.

We welcome applicants from all backgrounds and evaluate each candidate based on merit, regardless of personal characteristics such as age, gender, origin, religion, sexual orientation, neurodiversity, or disability.