AI Governance Program Manager

Location:- New York City (Primary Location)/Jersey City, NJ (Secondary Location)

Role AI Governance Program Manager

Job description :

Key Responsibilities

AI Governance Program Manager

This is a position for a hands-on program manager responsible for AI governance operations and process maturity within a regulated, financial services environment.

Role Overview / Summary

The AI Governance Program Manager will establish and refine AI governance processes and actively run the ongoing governance program. This role owns end-to-end governance for AI use case intake, evaluation, approvals, and oversight, ensuring consistent decisioning and clear accountability across stakeholders.

The role facilitates evaluation of AI use cases across key dimensions including commercial viability and value, risk (including model risk, operational risk, and regulatory risk), strategic alignment, and platform or tool choice. The Program Manager coordinates across business and control functions to ensure auditability, traceability, and well-documented governance outcomes.

Key Responsibilities

• Design and or refine the AI governance framework, operating model, and RACI for AI use case intake, evaluation, approval, and ongoing oversight.
• Build and operationalize intake processes, templates, and review criteria, including defining minimum required submission artifacts and quality bars for review readiness.
• Facilitate the AI use case approval lifecycle end-to-end, from initial submission through final approval, including managing rework cycles, decision conditions, and remediation requirements.
• Establish and enforce governance checks and balances through defined checkpoints, including initial triage, risk review, legal and privacy review, information security review, architecture and platform review, and final approval.
• Run governance cadences, including scheduling, agenda creation, pre-read preparation, meeting facilitation, decision capture, action tracking, and follow-ups to closure.
• Coordinate with Risk, Compliance, Legal, Privacy, InfoSec, Technology and Architecture, Data, and Business stakeholders to ensure each governance dimension is evaluated thoroughly and consistently.
• Maintain a centralized governance backlog and portfolio view, including status tracking, approvals, conditions, exceptions, waivers, and remediation actions with clear owners and due dates.
• Maintain a decision log with traceability of rationale, reviewers, approvals, conditions, and required evidence to support audit and regulatory inquiries.
• Define, monitor, and report governance metrics to demonstrate throughput and effectiveness, such as intake volume, cycle time, approval rates, bottlenecks, and recurring issues.
• Ensure documentation standards and evidence collection practices are consistently applied, supporting readiness for internal audit, risk challenges, and regulatory examinations.
• Support change management and communications for new or updated governance processes, including stakeholder enablement, rollout planning, and ongoing process reinforcement.

Required Skills & Qualifications

• Proven program management experience in governance, risk, compliance, or technology controls within a regulated environment, preferably financial services.
• Demonstrated ability to build and operationalize governance processes and operating procedures, including driving adoption and execution, not only documenting frameworks.
• Strong facilitation skills for senior forums, with the ability to drive decisions, manage conflict, and resolve cross-functional ambiguity while maintaining appropriate challenge and independence.
• Working knowledge of AI and ML lifecycle concepts and typical enterprise risk concerns, including data privacy, model risk, security, third-party risk, bias and fairness considerations, and monitoring expectations.
• Experience managing intake pipelines, workflow tooling, and producing executive-ready governance reporting with clear status, decisions, risks, and asks.

Preferred / Nice-to-Have Skills

• Experience with AI governance frameworks and model risk management concepts.
• Experience establishing or running AI use case review boards, steering committees, or similar governance bodies.
• Familiarity with platform selection and architecture review processes for analytics and AI solutions.
• Experience authoring policies and procedures and supporting enterprise controls testing or assura…