About The Project (description, Duration, Stage)
Hands-on AI-for-Security engagement with a regulated iGaming / online-gaming group. The client's security team is genuinely advanced: they already run an AI-driven offensive-security capability — continuous external-perimeter scanning feeding an LLM agent that plans exploitation, sources and validates exploits, and executes them in sandboxed environments — plus a runtime anomaly-detection layer watching for intrusion and privilege-escalation patterns across their products. They built this themselves and have explicitly asked us to challenge and improve it, not just rubber-stamp it.
This is not a generalist AI project. Neurons Lab brings the AI‑architecture and engagement depth; what's missing is the offensive‑security domain lead who can sit across the table from a hands‑on CISO team as a peer, pressure‑test their pipeline, and own the methodology. You are that expert. The early work is concrete and consultative: understand what they've built, find where it's wrong or expensive, and propose a better way.
Stage:



pre‑engagement / discovery (the immediate next step is a joint technical session with the client's CISO / security engineers). Duration: discovery → advisory / PoC, with strong extension probability as the security program scales across the group.
Reporting: Neurons Lab CTO / engagement lead (@Alex Honchar); partners with the Neurons Lab AI Architect on the account. You are the security domain owner for this track.
What You’ll Actually Do (example Tasks)

Join joint working sessions with the client's hands‑on security engineers; challenge and harden their AI‑driven offensive pipeline end‑to‑end (recon → verification → AI‑planned exploitation → sandboxed execution).
Design and refine the exploitation agent: how the LLM plans attack paths, selects and validates exploits, and orchestrates parallel sandboxes safely and reproducibly.
Optimise cost‑per‑finding of the existing exploitation pipeline: benchmark local /

📌 AI Architect (Madrid)
🏢 Neurons Lab
📍 Madrid