AI Governance Program Manager

Role: AI Governance Program Manager

Location: New York City /Jersey City, NJ (Onsite)

Duration: W2 Contract (Independent candidates on W2)

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 assurance activities.

Core Competencies

• Governance operating model design and continuous process improvement.
• Stakeholder orchestration across business, technology, and control functions.
• Risk-informed decision facilitation and structured escalation management.
• Documentation and evidence management to support traceability and audit readiness.
• Portfolio and backlog tracking with disciplined action management.
• KPI definition, governance reporting, and executive communications.

Soft Skills & Professional Attributes

• Executive presence and strong facilitation skills with senior stakeholders.
• Highly structured thinking and ability to translate ambiguity into clear process, decisions, and actions.
• Diplomacy and the ability to challenge constructively while maintaining productive cross-functional relationships.
• High attention to detail, particularly in decision capture, conditions, evidence, and auditability.
• High ownership and accountability, with the ability to operate with urgency and independence in a contractor capacity.

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 n…