Objective
Make AI adoption across the group's eight engineering organizations continuous and rhythmic: cascade each CTO's vision into their teams as working discipline, and move practices that already work in one company into the other seven.
Objective
Make AI adoption across the group's eight engineering organizations continuous and rhythmic: cascade each CTO's vision into their teams as working discipline, and move practices that already work in one company into the other seven.
About The Project
Neurons Lab runs a group-wide AI Adoption Program for a major iGaming client: a holding of six game studios plus central business functions, 10+ companies, ~800–1,000 employees. The program combines business-team enablement, engineering enablement, and custom AI for game production.
This role owns the engineering enablement track exclusively — the direct counterpart of the AI Education/Engagement Manager, who owns business teams. It is a new role, additional to the squad's AI Architect on the game-dev track ;
it does not build game-production pilots.
The engineering organizations span the full maturity range — from production agentic workflows, custom MCP servers and an AI-gateway rollout in the strongest companies, to teams writing their first specs. Every company keeps its own tools (Cursor / Claude Code / Codex — diversity is deliberate policy);




this role transfers practices, not tools .
Duration: ongoing, client-dedicated. Stage: start.
KPIs
Diffusion (core): ≥2 practices packaged per month into reusable artifacts (playbook, spec template, skills repo, recorded demo);
≥3 cross-company transfers per month, each adopted by ≥2 further companies;
≤2 weeks from detectionto group-wide availability
Adoption: ≥1 experiment per active team per sprint ("no empty sprints");
weekly-active AI usage ≥80% of engineers per active company (targets calibrated after 30-day baseline)
Outcomes: developer time savings vs baseline;
PR throughput and lead-time trend (DX Core 4 / DORA);
guardrail — change failure rate and rework must not rise as AI share grows
Rhythm: bi-weekly validation calls and monthly cross-company demo meets held on cadence;
live one-page status board per company;
CTO satisfaction ≥8/10 on a quarterly pulse
Areas of responsibility
Inside each company: take the cascade load off the CTO — turn their vision into team-level discipline: specs, rules, review standards, reusable skills, onboarding of the next circle of engineers
Run the diffusion loop between companies: detect what already works in one team, validate direction and risks, package it into a reusable artifact,

📌 Technical Ai Engagement Lead (Madrid)
🏢 Neurons Lab
📍 Madrid