Building & Securing
Enterprise AI
Infrastructure

Documenting what it actually takes to design, deploy, and secure AI systems. From GPU network segmentation to governance-as-code to incident response playbooks — built by a practitioner with 20 years in cyber defense & infrastructure security.

20+
Years in Cyber Defense
5
Enterprise Artifacts
33
Security Controls
12
Video Episodes

Latest Episode

Why AI Infrastructure Needs Its Own Security Architecture

Enterprise AI infrastructure is being deployed at speed without security architecture designed for AI-specific threats. Traditional network security doesn't account for GPU cluster lateral movement, model weight exfiltration, training data poisoning, or inference endpoint abuse.

Video coming soon

Why AI Infrastructure Needs Its Own Security Architecture

Core Competencies

The skills behind the artifacts.

AI Security Architecture

  • MITRE ATLAS threat modeling
  • 5-layer defense-in-depth design
  • GPU cluster network segmentation
  • AI-specific SIEM rule development

AI Governance & Compliance

  • NIST AI RMF implementation
  • Governance-as-code (OPA/Rego)
  • EU AI Act compliance mapping
  • Model risk tiering frameworks

Infrastructure Engineering

  • Docker / Kubernetes orchestration
  • GPU infrastructure (NVIDIA ecosystem)
  • MLflow, LangChain, ChromaDB
  • Prometheus / Grafana monitoring

Security Operations

  • AI incident response playbooks
  • Supply chain security (Trivy, Sigstore)
  • Red team / adversarial testing
  • NIST CSF 2.0 program management

Built by Nicholas Vidal

AI Security, Cyber Defense & Compliance Architect with nearly 20 years of experience across federal and enterprise environments. Every artifact, every lab configuration, and every video in this series is backed by production-grade security engineering.