
Neurons Lab · Poland
REMOTE (EU TIME ZONES), REGULAR ON-SITE IN BRATISLAVA, MALTA AND CYPRUS THE ENGAGEMENT ABOUT THE PROGRAM Neurons Lab is running a group-wide AI Adoption ...
REMOTE (EU TIME ZONES), REGULAR ON-SITE IN BRATISLAVA, MALTA AND CYPRUS
Neurons Lab is running a group-wide AI Adoption Program for a major client: a holding of six game studios plus central business
functions (Legal, Finance, Commercial, HR, Marketing), with 10+ companies in total in the group. The program combines business
team enablement, engineering enablement, and custom AI agents for game production.
This role leads AI enablement of the business teams exclusively. It does not deliver the engineering or game production tracks:
those are owned by separate technical teams. The focus here is taking each business team from first assessment through workshops
and hands-on enablement to self-sufficient daily use of AI.
Lead AI enablement for the client's business teams end to end: conduct assessments, find pain points and solve them, deliver
workshops personally, facilitate sessions with external trainers for specialist topics, activate stakeholders and champions, track
adoption KPIs, and stay in the client's context every day until each team runs on its own.
any enablement is planned.
enablement plans, working AI skills, or recommendations for specialist tools.
training, or an engineering opportunity to hand to the technical track.
value is in the entire flow, including before and after the workshop.
a two-week support window, and a follow-up review call for every workshop.
skills, prompts, and tools the team uses the next day.
domains), brief them, facilitate their sessions, and hold them to the quality bar.
leadership so momentum is seen at the top.
value), and design interventions. Bottom-up engagement, not top-down mandates.
sessions per team (weekly or bi-weekly), and never let context go stale on either side.
report progress transparently to the client and internally.
usage without support.
in one company propagate across the group.
the client's business. This role goes deep inside the business teams on adoption, engagement and change.
those tracks are owned by separate technical teams. Where real engineering is needed, they route it to the architect and
engineering team.
conduct workshops, facilitate the sessions run with external trainers, and own the entire flow before and after each workshop.
own, adapt on the fly to the audience in the room, and make complex AI topics practical for non-technical teams.
understands the psychology of engagement and how to make change stick from within.
engineering); can decompose an expert's workflow and rebuild it as an AI-assisted process together with that expert, including
for non-technical audiences.
assessments, feedback sessions and executive updates; able to work with everyone from senior lawyers to game designers.
converts into long-term value for the client.
splitting attention across multiple projects.
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 detection to 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, transfer it to the rest, measure against objective criteria * Operate the rhythm: bi-weekly validation calls with active teams (an empty sprint is a signal to reorganize, not to push harder), a monthly cross-company demo meet, a per-company status board, and a monthly steering sync with the group CTO * Teach teams to define objective, numeric success criteria for agentic work (loop engineering / hill-climbing against a metric) — the single biggest success factor for agents in production * Respect each company's protocols: work through the local CTO first (some CTOs require being the first point of contact for all technical topics), never around them * Triage needs that exceed enablement into scoped units — workshops (with the Head of AI Engineering), PoCs, deep-dive reviews — and hand them to the right Neurons Lab team * Feed the group-level gateway/attribution agenda: cost and error attribution per team and tool; collaborate with the cloud team on cost optimization and AWS credits/co-funding * Capture everything reusable in a group knowledge base; make wins visible to the CTOs and group leadership SKILLS * Hands-on daily fluency with agentic coding stacks: Claude Code, Cursor, Codex — including MCP servers, skills, sub-agents, and spec-driven development on real repositories * AI architecture: LLM gateways/proxies (LiteLLM / OpenRouter class), cost and error attribution, local-LLM trade-offs, in-region deployment patterns (e.g. Bedrock) * Engineering-leadership credibility at tech-lead / AI-architect / head-of-engineering level — able to review real code, pipelines and specs with senior engineers, not present slides * Facilitation of technical sessions: live demos, validation calls, hands-on workshops with real repos * Packaging: turning a working practice into an artifact another team adopts without the author in the room KNOWLEDGE * Engineering measurement in the AI era: DX Core 4 / DORA, AI-impact metrics, quality guardrails for AI-generated code * Adoption psychology for senior engineers — resistance among seniors is a named blocker in several of the client's companies * Game development / iGaming exposure (nice to have): game math, certification constraints, art/animation pipelines EXPERIENCE * Led AI adoption or platform/developer-enablement work in an engineering organization (20+ engineers), or equivalent tech-lead/head-of-engineering experience * Shipped agentic workflows to production; can show their own skills, MCP servers or spec repositories * Fluent English required; Russian and/or Ukrainian a strong plus — the client's teams communicate in both
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