Head of AI Governance -Vice President
Role details
Job location
Tech stack
Job description
The Head of AI Governance (Vice President) will lead governance for AI solutions across HR + Employee Experience (EX), reporting into the HR/EX Chief Data & Analytics Office (CDAO). This role owns the end-to-end governance "funnel"-from intake and triage of data/AI use cases, through cross-functional review forums, to final disposition and ongoing tracking / audit -ensuring solutions are fit-for-purpose, compliant, scalable, and aligned to business value. The role will operate a broader AI Governance Forum, partnering closely with CDAO AI & Data Science, CDAO AI Evaluation & Testing, Finance Business Management, Compliance/ Risk/ Controls/ Legal, and HR/EX Product Management., * Create and operationalize a broader AI governance cadence covering new and evolving AI solutions (build/buy/partner).
- Orchestrate cross-functional governance execution
- Act as the "quarterback" across stakeholders to shepherd reviews to completion and prevent stalled decisions.
- Establish expectations on roles & responsibilities, SLAs, escalation paths, and required review checkpoints.
- Build governance transparency and workflow tooling ("pizza tracker")
- Implement a governance "pizza tracker" to provide product managers and stakeholders clear visibility into:
- Align AI solutions to job architecture and workforce impact lens
- During governance reviews, map solutions and the tasks they perform to the job architecture matrix.
- Identify which existing job families/roles may be impacted (task substitution, augmentation, or workflow redesign) and ensure relevant stakeholders are engaged as needed.
- Support clear documentation of operating model impacts, change management considerations, and adoption readiness.
Requirements
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7+ years of experience in one or more of: data governance, AI governance, risk management, compliance, controls, product governance, or technology governance within a large, regulated organization.
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Demonstrated success building and running cross-functional governance forums and managing complex approval workflows.
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Working knowledge of AI/ML lifecycle concepts (model development, evaluation/testing, deployment, monitoring) and associated governance considerations.
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Strong understanding of data use risk domains (e.g., privacy, security, third-party risk, data classification, retention, access controls), and ability to translate into pragmatic governance processes.
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Exceptional stakeholder management skills-able to influence without authority, drive closure, and handle competing priorities.
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Strong program management discipline: structured thinking, documentation rigor, operational cadence, and metrics-driven execution.
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Experience designing workflow tooling / automation (e.g., intake portals, trackers, structured templates) strongly preferred.