Cybersecurity AI Risk and Governance Director

Vantage Data Centers

Cybersecurity AI Risk and Governance Director at Vantage Data Centers ensuring security for AI, ML, and LLM systems. Leading AI cybersecurity initiatives for operational and enterprise environments.

Posted 4/24/2026full-timeDenver • Colorado, Virginia • 🇺🇸 United StatesLead💰 $200,000 - $220,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityGoogle Cloud Platform

About the role

Key responsibilities & impact

Establish enterprise governance for detection, classification, and management of unauthorized (shadow) AI across business units
Define and enforce security architecture standards for AI, ML, and LLM platforms across cloud, hybrid, on-prem, and OT-adjacent environments
Provide security design oversight and approval for AI systems, including data pipelines, model hosting, inference paths, APIs, and integrations
Define enterprise methodology for AI security assessment covering architecture, design, and implementation across applications, agents, and workflows
Ensure AI architectures enforce segmentation, least privilege, deterministic behavior, and fail-safe operation, particularly where OT or critical infrastructure data is involved
Establish AI-specific incident response playbooks and lead response to AI-related security, safety, or governance incidents
Enforce controls preventing unauthorized model retraining, autonomous learning, or use of live production or OT data outside approved intent
Define security requirements for explainability, traceability, and output validation where AI influences operational, workforce, safety, or compliance outcomes
Drive alignment with ISO 42001 and related AI governance standards across applicable teams
Enforce protections against prompt injection, data leakage, hallucination risk, unauthorized context expansion, and external model training exposure
Ensure sensitive enterprise, operational, personnel, and contractual data is not exposed to or retained by external AI platforms without approved safeguards
Approve and oversee AI data ingestion pipelines, enforcing purpose limitation, data minimization, and classification requirements
Validate encryption, access logging, retention, and deletion controls for data used by AI systems
Define and enforce controls preventing cross-domain data correlation that violates trust boundaries or governance constraints
Perform AI-specific threat modeling, including risks such as data poisoning, model theft, inference abuse, output manipulation, and decision integrity compromise
Integrate AI threats into enterprise cybersecurity and OT risk models, including definition of compensating controls and escalation for systems exceeding risk tolerance
Own and maintain the AI risk register covering confidentiality, integrity, availability, explainability, data quality, model drift, adversarial attacks, and business impact
Ensure AI systems generate telemetry, logging, and audit trails sufficient to detect misuse, drift, or anomalous behavior
Integrate AI security monitoring into SOC, SIEM, and enterprise incident response workflows
Enforce prohibitions on autonomous AI control of OT assets, including power, cooling, BMS, fire suppression, and physical access systems
Validate one-way data flows, read-only access models, and manual override requirements where AI consumes OT telemetry
Partner with OT and infrastructure teams to ensure AI enhances visibility and decision support without compromising safety, reliability, or uptime
Oversee security reviews of vendor-provided and embedded AI capabilities, including model behavior, data handling, and contractual protections
Define and enforce minimum security and governance requirements for AI vendors, including audit rights and termination conditions

Requirements

What you’ll need

Bachelor’s degree in Cybersecurity, Computer Science, Data Science, Engineering, or related field, or equivalent experience
Minimum 10+ years of experience in cybersecurity, security architecture, or risk engineering roles
Hands-on experience securing data pipelines, APIs, cloud platforms, and analytics or ML-enabled systems
Strong understanding of identity, access management, encryption, logging, and secure system design
Direct experience securing AI/ML platforms, LLMs, or analytics pipelines (preferred)
Experience with cloud security (Azure, AWS, GCP) and SaaS-based AI platforms (preferred)
Familiarity with OT, critical infrastructure, or safety-critical environments (preferred)
Security certifications such as CISSP, CCSP, CISM, or cloud security certifications (preferred)

Benefits

Comp & perks

medical, dental, and vision coverage
life and AD&D
short and long-term disability coverage
paid time off
employee assistance
participation in a 401k program that includes company match
many other additional voluntary benefits

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

cybersecuritysecurity architecturerisk engineeringdata pipelinesAPIscloud securityencryptionloggingsecure system designAI/ML platforms

Soft Skills

leadershipcommunicationorganizationalincident responseoversightcollaborationproblem-solvingrisk assessmentmethodology developmentstakeholder engagement

Certifications

CISSPCCSPCISMcloud security certifications