About the project
The client is a group of iGaming companies (multiple game studios and providers, incl. slot-game studios) whose shareholders engaged Neurons Lab to accelerate AI adoption across the whole group — not just one studio. We have completed the assessment phase (interviews and workshops across studios), delivered a working prototype for AI-assisted game production, and are now entering a paid pilot with the first studios.
The engagement is prototype-first: the client's C-level and product owners expect working code and live demos, not slides. The core technical direction is agentic AI applied to real game production — game math engines, game logic (backend), and game client code — and a shared, transferable AI layer that benefits every studio in the group.
This is a Talent Network engagement (freelance contract), not a full-time position. Allocation is 0.5+ FTE, with strong preference for a candidate available closer to full-time — ideally one person covers both architecture and hands-on engineering.
Objective
- Act as the embedded technical lead for AI on the account: design, build, and demo production-grade agentic AI solutions for game development
- Deliver fast, visible results that benefit the group of companies as a whole (shared AI layer across studios), not only a single studio
- Transfer knowledge continuously to the client's teams and to Neurons Lab engineers
Areas of Responsibility
Technical Architecture & Hands-on Implementation
- Build working prototypes and pilots on the client's real game stack — mathematical engine, game backend, and client — so product owners can test game ideas at scale on real math, not simplified mocks
- Design and implement custom agentic setups ("harness + loop + graph") that are transferable between AI systems (Claude Code / Codex / Cursor and similar), beyond what off-the-shelf tools provide
- Own the technical architecture: model selection, deployment patterns, infrastructure, cost estimation (incl. token economics), and monitoring
- Prepare and run technical demos; always keep a fallback (recorded demo, whitelisted environment) so a live session never fails
- Produce follow-up technical packs after client sessions: flows, component schemas, deployment views, cost estimates
Working with Client Stakeholders
- Present technical solutions with concrete focus on the actual system being built — avoid abstract industry examples and generic "challenges software teams face" talking points
- Engage confidently with senior, technically strong client-side stakeholders (CTO-level scrutiny is the norm on this account); articulate clearly why our approach is better than the tools the client already knows
- Respect role boundaries: product feature decisions belong to the product/delivery lead, and commercial topics (what we sell, engagement model) belong to the account team — the architect's voice is decisive on technical excellence, architecture, and implementation
- Accept decisions once they are made and move forward — collaborative, low-ego working style with quick debriefs and fast iteration
Team & Knowledge
- Lead and unblock AI engineers on the project where present; create tasks, review output, share feedback
- Run knowledge transfer sessions so the team is never a single point of failure
- Support proposal preparation with technical input (estimates, architecture options) when asked by the account team
Experience
- iGaming / game-development domain expertise — mandatory. Hands-on familiarity with slot/casino game production: game math engines (RTP, volatility, balancing), game logic and backend, game client. This is the primary reason the role is open — generic AI expertise without gaming domain knowledge is not sufficient for this client.
- 7+ years hands-on AI/ML development, incl. strong recent agentic AI practice: building harnesses, loops, multi-agent systems, and AI developer-tooling on top of Claude / Codex / Cursor-class systems.
- Prototype-first delivery record. Can show (not tell) existing work: working skills, tools, agents, and loops that operate strictly on code and math. Candidates will be asked to demo real artifacts during the interview.
- Consulting / client-facing seniority. Experience as a technical lead in front of demanding enterprise or product-company stakeholders; confident and proactive (not defensive) under challenge from strong internal engineering teams.
Nice to have:
- Experience delivering to a group/holding structure or multi-brand organization (shared platform serving several business units)
- Game art/graphics pipeline understanding (not required to work on it, but useful for context)
- Cloud hyperscaler experience (AWS / Azure / GCP — all equally valid)
