[Hiring] AI Architect @Neurons Lab

Role Description

Hands-on AI-for-Security engagement with a regulated iGaming / online-gaming group. The client's security team is genuinely advanced:

• They 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.
• A runtime anomaly-detection layer watching for intrusion and privilege-escalation patterns across their products.

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.

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.

Qualifications

• Hands-on offensive security: vulnerability research, exploit development and chaining, web + network penetration testing.
• Building and operating LLM agents for security work.
• Local / self-hosted open models: running and tuning open weights on rented or private GPU.
• Exploit & threat intelligence: sourcing and validating exploits, CVE triage.
• Runtime detection: designing intrusion / privilege-escalation pattern detection.
• Cloud security (AWS preferred): sandboxing, container isolation, secure inference hosting.
• Writes their own code (Python + shell) and can explain methodology to non-security executives.

Requirements

• Modern offensive-security methodology and the current exploit / zero-day landscape.
• Strengths and limits of frontier vs. local LLMs for security automation.
• Data-egress / sovereignty constraints: why IP and recon-enabling data must stay in-perimeter.
• iGaming / regulated-infrastructure context and certification constraints — strong plus.
• Defensive side — SIEM, anomaly detection, incident response — plus.

Experience

• Key characteristics (ideally 4/4):
• Hands-on offensive security.
• Built or operated AI / LLM-driven security automation.
• Cloud hyperscaler experience (AWS preferred).
• Technology consulting / client-facing delivery — can lead a CISO-level technical conversation.
• Role-specific characteristics:
• 3+ years hands-on offensive security / vulnerability research / red-team.
• Demonstrable exploit development and chaining; comfortable with zero-day research and exploit intelligence.
• Has wired LLMs into real security workflows.
• Has run self-hosted / local open models in a real engagement, with a view on cost and hardware.
• Comfortable being the sole domain expert in the room and owning the methodology.

Terms & Conditions

Allocation: ~0.25 – 0.5 FTE initially (discovery/advisory + joint CISO sessions), scaling with the engagement.