The role

We're looking for a unique blend of hands-on software engineer and passionate technical educator to drive our internal AI transformation. You'll turn generic AI capabilities into company-specific leverage - setting up reliable tooling, defining security guardrails, and creating comprehensive learning paths. You'll act as the central bridge between engineering and the broader business, championing AI adoption and shifting workflows across departments.

If you love exploring LLMs, building prototypes, and have a talent for explaining complex concepts in a way that genuinely empowers others, this role will give you direct impact on the productivity and culture of the entire organisation.

What you'll own

AI Tooling Setup - hands-on installation and integration of AI tools (Claude, Copilot, Cursor) with internal systems via MCP servers to build context-aware, reliable AI workflows
Phased AI Adoption - lead rollout starting with engineering, then expand to non-technical departments
Enablement Programmes - training curricula, playbooks, workshops, and self-serve documentation to upskill the entire company on LLMs
AI Standards & Best Practices - prompting guidelines, AI-ready documentation, reusable workflow patterns to make AI usage predictable and effective across teams
AI Champion Network - identify, train, and support local AI advocates across teams to multiply adoption horizontally
Security Guardrails - partner with Security, IT, and Legal on data privacy and prompt hygiene defaults
Tool Evaluation - evidence-based methodology for selecting AI tools benchmarked against real workflows
Impact Measurement - track AI adoption metrics and show where AI creates real leverage
Hands-on Credibility - stay deeply technical by prototyping integrations, dogfooding tools daily, and building reference workflows; your credibility rests on doing the work, not just teaching it
Travel - occasional office visits to run in-person workshops, onboard teams, and collaborate directly with engineers and stakeholders

What you bring

Technical:

5+ years of hands-on software engineering experience - engineering fluency matters more than specific stack
1+ year of deep, hands-on LLM experience (Claude, GPT, etc.) - prompt design, agentic workflows, real-world model limits
Proven experience configuring or building AI-assisted developer tools (coding assistants, RAG, agents)
Strong API integration skills and solid Git workflows
Sound understanding of data security, privacy, and access-control basics

Soft skills & mindset:

Exceptional communication - you write playbooks and training materials people actually use (this is a communication-first role)
Proven experience in mentoring, technical onboarding, running internal talks, or building communities of practice
Influence without authority - you build enthusiasm, drive adoption, and shift behaviours across teams that don't report to you
Comfortable facilitating workshops and presenting to groups
Proactive, highly analytical, and comfortable defining your own roadmap in an ambiguous space
Polish at C1 level - required
English at C1 level strongly preferred (B2 minimum)

Nice to have:

Hands-on experience with Claude, Cowork, and MCP (Model Context Protocol)
Background in Developer Advocacy, Developer Relations, or formal internal technical enablement
Experience creating formal technical documentation, courseware, or developer-facing content
Familiarity with React/Next.js for building internal tools and demos
Comfort with SQL and exposure to NoSQL or vector databases
Working knowledge of Docker, CI/CD, and containerised environments