AI Enablement Lead (iGaming)

TL;DR

AI Enablement Lead (AI Engineering): Driving the adoption of internal AI platforms by coaching and upskilling technical teams to build and deploy self-sufficient AI solutions with an accent on RAG, AI agents, and governance. Focus on bridging the gap between early adopters and mainstream usage, designing hands-on workshops, and embedding security and compliance into the AI lifecycle.

Location: Hybrid (London, UK)

Company

hirify.global is one of Europe’s leading betting and gaming operators, operating in around fifteen regulated markets with a focus on technological excellence and safety.

What you will do

• Design and deliver hands-on technical workshops where engineers build and ship working AI agents independently.
• Coach product and engineering teams in scoping and delivering AI use cases using the internal KAIT platform.
• Create technical training content covering RAG, AI agent design, prompt engineering, and API integration.
• Ensure security, data governance, and compliance are embedded into every use case from the start.
• Conduct AI opportunity audits within Tech teams to identify quick wins and strategic projects.
• Promote the adoption of coding assistants like GitHub Copilot and Cursor across engineering teams.

Requirements

• Must be based in or able to work hybrid in London, UK.
• 4–7 years in a hands-on technical role (Data Engineering, AI/ML Engineering, Solutions Architecture, or DevOps).
• Proven experience coaching technical teams to deploy AI agents or RAG pipelines in production.
• Hands-on experience with low-code/no-code automation platforms, specifically n8n.
• Deep knowledge of prompt engineering (chain-of-thought, structured output) and enterprise integration patterns (REST APIs, OAuth).
• Strong commitment to governance, data classification, and production release processes.

Nice to have

• Experience in regulated industries such as iGaming or Fintech.
• Familiarity with Model Context Protocol (MCP) or similar frameworks for connecting AI agents to enterprise systems.
• Experience with LLM providers (OpenAI, Anthropic) and vector databases.
• Experience with developer productivity tools (GitHub Copilot, Cursor).

Culture & Benefits

• Hybrid work model allowing for self-organization and flexibility.
• Opportunity to define AI adoption standards for a technical function of over 1,000 people.
• Work in a high-stakes, regulated environment where security and governance are prioritized.
• Company culture that views career growth as a marathon, valuing the person first.