AI Education / Engagement Manager

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 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. Mission Lead AI enablement across the group 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. Scope Key Responsibilities Assessments & pain points Conduct assessments: run structured assessments with each business team to map workflows, skills, and current AI usage before any enablement is planned. Find and solve pain points: collect the team's real pain points and use cases, prioritize them, and turn them into concrete enablement plans, working AI skills, or recommendations for specialist tools. Triage each use case: a skill to build with the team in hours or days, an off-the-shelf specialist tool to introduce plus training, or an engineering opportunity to hand to the technical track. Workshops & enablement delivery Holistic AI enablement trainer: conduct workshops personally, and facilitate the sessions delivered with external trainers. The value is in the entire flow, including before and after the workshop. Own the workshop lifecycle end to end: pre-assessment, workshop design aligned with the client, delivery, feedback collection, a two-week support window, and a follow-up review call for every workshop. Deliver concrete outcomes: ensure every workshop targets the team's own use cases and produces walk-away artifacts: working skills, prompts, and tools the team uses the next day. Engage external trainers: bring in specialist trainers on demand for specific workshops (commercial, creative, legal, and other domains), brief them, facilitate their sessions, and hold them to the quality bar. Stakeholder activation & change management Activate champions: identify champions inside each team, work with them 1:1, and make their results visible to client leadership so momentum is seen at the top. Remove adoption blockers: run feedback and bonding sessions, surface what stops people from using AI (fear, skill gaps, unclear value), and design interventions. Bottom-up engagement, not top-down mandates. Stay in the client's context: maintain daily contact with the business teams across the group, keep a recurring cadence of sessions per team (weekly or bi-weekly), and never let context go stale on either side. KPIs & reporting Assess and track adoption KPIs: set realistic adoption targets per team, measure actual usage after each enablement cycle, and report progress transparently to the client and internally. Release teams as self-sufficient: define what "done" looks like for each team and hand over ownership once the team sustains AI usage without support. Feed the pipeline: pass engineering-grade opportunities to the technical teams and capture reusable skills and assets so wins in one company propagate across the group. Boundaries What This Role Is Not Not the Account Delivery Manager. The Delivery Manager owns overall account coordination and is the single point of contact for the client's business. This role goes deep inside the business teams on adoption, engagement and change. Not a software delivery role. This person does not build custom AI agents for game production or any engineering deliverables; those tracks are owned by separate technical teams. Where real engineering is needed, they route it to the architect and engineering team. Not only a trainer, a holistic AI enablement trainer. This person orchestrates trainers and owns adoption outcomes: they conduct workshops, facilitate the sessions run with external trainers, and own the entire flow before and after each workshop. Profile Who We Are Looking For Skilled trainer: a strong, experienced trainer who can design and deliver engaging workshops and training sessions on their own, adapt on the fly to the audience in the room, and make complex AI topics practical for non-technical teams. Change management and adoption background: hands-on experience driving technology or process adoption inside organizations; understands the psychology of engagement and how to make change stick from within. Practical AI fluency: confident daily user of modern AI tools (Claude, ChatGPT, agentic workflows, skills and prompt engineering); can decompose an expert's workflow and rebuild it as an AI-assisted process together with that expert, including for non-technical audiences. Facilitation and communication: experienced in delivering workshops and training sessions personally, and comfortable running assessments, feedback sessions and executive updates; able to work with everyone from senior lawyers to game designers. Strategic thinking: can design an engagement program, not just execute tasks; sees which use cases matter and how adoption converts into long-term value for the client. Energy and ownership: high-energy, genuinely enthusiastic about AI, fully committed to one client. Not a role for someone splitting attention across multiple projects. Languages: fluent English; Russian or Ukrainian is a strong plus given the client's teams. Nice to have: iGaming or game development exposure; experience with enablement or training businesses; consulting background. Outcomes Success metrics Post-workshop adoption per team (primary KPI): teams actively using AI in daily work after the support window closes. Champions: number of active champions identified, developed, and made visible to client leadership. Cadence adherence: recurring sessions held on rhythm; response times measured in hours, not days. Self-sufficiency and pipeline: teams released as self-sufficient; qualified opportunities passed to the technical tracks. Engagement growth: follow-up workshops, recurring enablement, and new scopes originating from business team engagement. What we offer Competitive compensation — a monthly base plus expansion revenue upside Fully remote — outcomes over attendance Unlimited PTO Full-time contractor engagement with a fast-growing AI consultancy at the forefront of enterprise transformation