SVP, AI Governance Lead

BNY Mellon•New York, NY

1d•$104,000 - $195,000•Onsite

About The Position

We are seeking a senior AI Governance leader to help design and strengthen governance frameworks for AI use cases across the enterprise. This role will partner with business, technology, risk, legal, compliance, and control stakeholders to support the responsible, well-controlled, and compliant adoption of AI.

Requirements

Bachelor’s degree in computer science, information technology, mathematics/statistics or the equivalent combination of education and experience is required.
7-10+ years of experience in governance, risk, controls, compliance, data management, technology risk, or related disciplines.
5+ years of leadership experience managing teams or enterprise governance, risk, or control programs.
Strong understanding of AI governance, lifecycle controls, risk management frameworks, and responsible AI principles.
Experience designing or implementing governance frameworks in complex enterprise environments.
Strong knowledge of control design, issue management, audit and regulatory engagement, and risk escalation practices.
Excellent stakeholder management, communication, and influencing skills.

Nice To Haves

Financial services industry experience.
Experience with AI risk, model risk management, operational risk, compliance, or technology control frameworks.
Familiarity with emerging regulatory expectations related to AI, model governance, privacy, and data usage.
Experience working with governance bodies, approval forums, or control committees.
Knowledge of data governance, data quality, lineage, and metadata concepts as they relate to AI enablement.
Experience supporting enterprise AI adoption, governance tooling, or control automation initiatives.

Responsibilities

Partner with cross-functional stakeholders to implement enterprise AI governance strategies, standards, and policies.
Lead AI governance assessments and continuous improvement initiatives.
Define and maintain governance requirements for AI use cases across the lifecycle, from concept through deployment, monitoring, and retirement.
Identify, assess, escalate, and help mitigate AI-related risks, including model, data, operational, compliance, and reputational risks.
Monitor compliance with governance requirements, internal policies, and applicable regulatory expectations.
Ensure AI initiatives are documented with clear business purpose, ownership, testing results, control evidence, and monitoring requirements.
Support governance of key AI assets, including datasets, models and workflows.
Partner with AI initiative owners, developers, data teams, and control stakeholders to embed governance throughout the AI lifecycle.
Support review and approval processes for new AI initiatives and material changes to existing capabilities.
Provide reporting on governance adoption, risk themes, control issues, and remediation progress.
Lead stakeholder engagement, governance forums, and cross-functional communications.
Support audit, regulatory, and governance committee engagement related to AI initiatives.