AI Security Architect

Overview

Hybrid
Depends on Experience
Contract - W2
No Travel Required

Skills

Artificial Intelligence
Auditing
Bridging
CISSP
Cisco Certifications
Collaboration
Communication
Computer Networking
Computer Science
Cyber Security
Data Science
Data Security
Docker
Encryption
FOCUS
GPU
HPC
Hardening
High Performance Computing
Hosting
Identity Management
Kubernetes
Lifecycle Management
Machine Learning (ML)
Network
Regulatory Compliance
Risk Assessment
Security Architecture
Security Controls
Threat Modeling
Vulnerability Management
Workflow

Job Details

Role Summary / Description:

We are seeking a highly skilled AI Security Architect to lead the design, implementation, and governance of security solutions across advanced AI platforms and infrastructure. This role will focus on ensuring secure architecture and operational practices for large-scale AI systems, including environments leveraging NVIDIA DGX SuperPODs, high-performance computing (HPC), and GPU-accelerated AI workloads.

As an AI Security Architect, you will work cross-functionally with infrastructure, data science, and platform engineering teams to deliver secure-by-design AI environments. You will provide deep technical expertise in security architecture, zero trust principles, data protection, and AI-specific threat modeling, ensuring compliance with internal policies and external regulations. You will also lead or contribute to the secure deployment and operational hardening of NVIDIA SuperPODs and their associated tools and frameworks.

This is a strategic and hands-on role that bridges enterprise security architecture with the unique demands of AI/ML platforms at scale.

Key Responsibilities:

  • Architect, design, and implement secure infrastructure for AI platforms, including NVIDIA DGX/SuperPOD environments.
  • Develop and enforce security architecture standards and best practices for AI workloads and high-performance compute (HPC) systems.
  • Conduct risk assessments and threat modeling for AI-specific architectures, data pipelines, and model lifecycle management.
  • Collaborate with platform engineering and data science teams to embed security controls into the ML lifecycle.
  • Lead the deployment and security hardening of NVIDIA AI infrastructure, tools, and networking components.
  • Evaluate and integrate third-party security tools and services tailored to AI/ML environments.
  • Drive security reviews and compliance assessments for AI platforms and assist in audits as required.
  • Provide security expertise across multiple domains, including identity & access management (IAM), network segmentation, encryption, vulnerability management, and monitoring in AI contexts.

Qualifications:

  • 5+ years of experience in cybersecurity architecture, with at least 2+ years focused on securing AI/ML platforms or high-performance computing (HPC) environments.
  • Proven hands-on experience with NVIDIA DGX systems and SuperPOD infrastructure, including the design, deployment, and operational hardening of these environments.
  • Deep familiarity with NVIDIA security tools, frameworks, and delivery models, including secure deployment and lifecycle management within SuperPOD environments.
  • Strong understanding of AI/ML workflows, data pipelines, and associated security risks across the model development and deployment lifecycle.
  • Experience implementing Zero Trust Architecture, identity and access management (IAM), and data protection strategies in distributed and hybrid compute environments.
  • Demonstrated ability to conduct threat modeling, risk assessments, and architecture reviews for complex AI systems.
  • Working knowledge of AI-specific compliance and governance requirements, such as secure model hosting, data residency, and auditability.
  • Familiarity with containerized and orchestrated environments (e.g., Kubernetes, Docker) and related security practices.
  • Strong communication and collaboration skills, with a history of working cross-functionally with platform, infrastructure, and data science teams.
  • Bachelor s degree in Computer Science, Cybersecurity, or related field (or equivalent practical experience). Advanced degrees or relevant certifications (e.g., CISSP, CCSP, GCSA) are a plus.
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