AI Security - Architect (AI & Cybersecurity Program)

Exl Neo Technologies
Chicago, IL, United States
13 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Software as a Service Cloud Computing Security Cyber Security Data Governance Data Infrastructure Identity and Access Management Network Segmentation Open Web Application Security Zero Trust Network Access
+9 more
Azure Machine Learning Sherwood Applied Business Security Architecture Google Cloud Large Language Models Togaf Deployment Automation Data Management Machine Learning Operations Data Pipelines

Job description

  • Define reference architectures and technical standards for secure AI/ML adoption (data governance, model lifecycle security, LLM/agentic AI security, network and identity boundaries).
  • Lead security architecture reviews for new AI initiatives, products, and vendor tools, identifying risks and required controls prior to launch.
  • Design enterprise patterns for AI guardrails, output validation, human-in-the-loop controls, and least-privilege access for AI agents and services.
  • Partner with enterprise architecture, data platform, and infrastructure teams to ensure AI security controls are embedded consistently across on-prem, cloud, and SaaS AI deployments.
  • Evaluate emerging AI security threats and technologies, advising leadership on architectural implications and roadmap priorities.
  • Mentor the AI Engineer team on secure design practices; provide technical governance over implementation to ensure alignment with architecture standards.
  • Contribute to AI governance policy, risk frameworks, and control mapping (NIST AI RMF, ISO/IEC 42001, OWASP LLM Top 10) from a technical architecture perspective.

Requirements

  • 8+ years in security architecture or enterprise architecture roles, including recent experience architecting controls for AI/ML or data platforms.
  • Deep understanding of AI/ML system design (data pipelines, model training/serving, MLOps) and associated security and privacy risks.
  • Strong grasp of cloud security architecture (Azure and/or AWS/Google Cloud Platform), identity and access management, network segmentation, and zero-trust principles.
  • Familiarity with AI governance and security frameworks: NIST AI RMF, ISO/IEC 42001, OWASP Top 10 for LLM Applications, and applicable data privacy regulation.
  • Demonstrated ability to communicate architecture decisions to both engineering teams and executive stakeholders., * Architecture certifications (SABSA, TOGAF) and/or security certifications (CISSP, CCSP).
  • Experience building AI/ML platforms or securing generative AI/agentic AI deployments at enterprise scale.
  • Retail or large consumer-brand enterprise experience.

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