Head of AI Governance

Responsibilities & Qualifications

• Own the operational governance gates for AI systems across the enterprise, ensuring AI solutions meet established quality, performance, and lifecycle standards prior to deployment and throughout production.
• Oversee AI-specific operational risks—including model drift, hallucinations, bias management, explainability implementation, and autonomous or emergent system behaviors—and work closely with AI delivery teams to ensure these risks are effectively managed.
• Report directly to the VP of Data, Analytics & AI and be based in Atlanta, GA, with an organizationally independent role to maintain governance objectivity, consistent with the governance independence principles outlined in the NIST AI RMF Playbook.
• Align AI governance practices with NIST AI RMF, ISO/IEC 42001, and applicable cross-border AI deployment regulations.
• Define and enforce quality and reliability standards for agentic AI behavior, including autonomous decision boundaries and exception handling.
• Oversee model validation, accuracy, robustness, and drift detection standards for all production AI models.
• Operate the AI model inventory and registry within the enterprise governance platform, Informatica Cloud Data Governance and Catalog (CDGC), ensuring all production AI models are cataloged, classified, and traceable.
• Own the AI use case intake process, including use case templates, architectural pattern validation, and model onboarding workflows.
• Own EU AI Act conformity assessment templates and geographic deployment scope tracking for all production AI systems.
• Own and maintain the AI-specific incident response playbook, including escalation protocols, root cause analysis, and remediation tracking.
• Define and enforce AI safety guardrail standards across all deployed AI systems.
• Coordinate with Cybersecurity on AI-related security incidents, maintaining clear escalation and handoff protocols.
• Define and enforce agent permission and tool scoping standards for both self-service agents and managed agents.
• Validate human-in-the-loop design compliance for all autonomous workflows prior to production deployment.
• Establish governance controls for multi-agent workflows, ensuring behavior predictability, auditability, and graceful degradation.
• Represent the AI governance function in the AI Steering Committee, executive forums, and cross-functional governance discussions.
• Translate regulatory and technical AI governance requirements into enforceable policies understood by business, engineering, and leadership audiences.
• Coordinate with Cybersecurity AI Governance to maintain clear, documented boundaries between platform governance and security governance responsibilities.
• Coordinate on configuration changes, access provisioning, and platform upgrade impacts to the AI governance module.
• Align AI data access requirements with the data classification, privacy, and entitlement standards enforced by Data Governance, ensuring AI systems access only appropriately classified and governed data.
• Maintain a shared escalation protocol with Data Governance for incidents at the intersection of data quality and AI model performance.
• Ensure the AI governance framework reinforces the enterprise Data & AI Governance framework without duplicating data governance controls.
• Contribute to quarterly planning, feature scoping, and sprint execution aligned to the enterprise delivery roadmap and KPI framework.
• Build strong working relationships with delivery teams, data governance, cybersecurity, legal, privacy, and business leaders to embed governance requirements into AI design, deployment, and operations.
• Enable adoption. Promote consistent understanding of AI governance expectations through clear communication, practical guidance, and measurable stakeholder engagement across the governance community.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Data Science, Information Systems, Law, or a related field.
• Minimum of 7 years of experience in AI governance, AI ethics, responsible AI, or AI risk management, with at least 3 years directly defining and operationalizing AI-specific governance frameworks.
• Demonstrated experience defining AI model audit protocols, explainability standards, bias testing procedures, or AI risk assessment methodologies.
• Working knowledge of AI/ML system lifecycles to serve as a credible governance authority with AI engineering teams.
• Familiarity with the AI regulatory landscape including the EU AI Act, NIST AI RMF, ISO/IEC 42001, or equivalent.
• Strong communication skills with the ability to translate regulatory and technical AI governance requirements into enforceable policies and represent the function in executive forums.

Preferred Qualifications

• Master’s degree or advanced certification in AI ethics, responsible AI, data science or law.
• Juris Doctorate.
• Certifications such as CAIP, ISO/IEC 42001 Lead Implementer, ISACA AI Fundamentals, or equivalent.
• Experience in manufacturing, industrial, or sustainability-focused organizations.
• Experience establishing AI governance programs from the ground up in organizations deploying AI at scale across multiple business functions.
• Experience governing enterprise generative AI tool adoption (e.g., Microsoft Copilot) including acceptable use policy development and output governance.
• Familiarity with TISAX certification requirements and cyber liability insurance considerations.
• Experience with cross-border AI deployment governance in multinational organizations.