AI Governance Program Manager
New
Based in the United StatesFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 5+ years of experience
- Required Skills
- ComplianceRisk ManagementStakeholder managementGenerative AI
Requirements
- 5+ years of experience in program management, compliance, risk management, legal operations, privacy, or business process coordination.
- Experience working across business, technology, legal, compliance, and risk stakeholders in complex environments.
- Strong understanding of governance, regulatory, or control frameworks in enterprise settings.
- Familiarity with AI, GenAI, or emerging technology governance concepts (certifications preferred).
- Strong organizational and process management skills with attention to detail and consistency.
- Ability to translate policy or abstract governance requirements into operational workflows.
- Excellent written and verbal communication skills, with the ability to engage both technical and non-technical audiences.
- Strong stakeholder management skills with the ability to coordinate across multiple teams and priorities.
- Analytical mindset with the ability to track processes, identify gaps, and improve operational efficiency.
- Ability to work in fast-paced, evolving environments where frameworks and standards continue to mature.
- Bachelor’s degree in Business, Information Systems, Risk, Operations, or a related field preferred.
Responsibilities
- Own and operate the end-to-end AI governance intake and execution process, ensuring all AI initiatives follow standardized workflows and documentation requirements.
- Translate enterprise responsible AI principles into practical governance steps, templates, and operational checkpoints.
- Coordinate governance reviews across Legal, Compliance, Privacy, Risk, Model Risk, and Enterprise Data & AI teams.
- Ensure AI use cases meet required documentation standards before progressing through key development and deployment milestones.
- Maintain the full AI governance lifecycle, from ideation and intake through production use, monitoring, and eventual retirement.
- Act as the central orchestration point for governance communications between technical teams and risk stakeholders.
- Track governance status, dependencies, and risks across multiple AI initiatives to ensure transparency and accountability.
- Improve governance workflows through process optimization, standardization, and tooling enhancements.
- Ensure consistency in governance artifacts, templates, and evidence collection across all AI projects.
- Support clarity of roles, responsibilities, timelines, and expectations for AI delivery teams and business sponsors.
- Monitor governance adherence and escalate gaps or risks to appropriate stakeholders.
- Enable scalable governance practices that support increasing AI adoption across the enterprise.
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