AI Governance Lead

Madison-Davis; New York (NY); On-site; USD 170,000 - 230,000; Full time

Job summary

Madison-Davis, LLC seeks an experienced AI Governance Lead to shape the enterprise framework, controls, operating model, and processes governing AI adoption. This hands-on leadership role spans AI/ML, Generative AI, LLMs, RAG, intelligent automation, and advanced analytics across the organization.

You will drive governance from concept to production, partnering with technology, risk, legal, and business domains, and translating regulatory expectations into practical, auditable procedures.

Qualifications

• 8+ years in AI governance, model risk, data governance, enterprise risk, or related areas.
• Direct experience designing or implementing enterprise AI governance.
• Experience operationalizing governance rather than only policy work.
• Strong understanding of AI/ML lifecycle management and Responsible AI.
• Experience in banking, financial services, insurance, fintech, or other highly regulated environments.

Responsibilities

• Design and operationalize enterprise AI governance frameworks, standards, controls, and processes.
• Establish governance for AI intake, inventory, risk assessment, technology review, approvals, monitoring, remediation, and reporting.
• Govern AI initiatives across lifecycle from ideation to production and retirement.
• Develop controls around data quality, privacy, lineage, explainability, human oversight, auditability, access, and resilience.
• Partner with technology, data, business, legal, risk, compliance, cybersecurity, audit, and operations teams.
• Establish governance for Generative AI, LLM, RAG, and advanced analytics solutions.
• Develop executive reporting around AI adoption, value, risk exposure, control effectiveness, and remediation.
• Translate policies and regulatory expectations into practical procedures and implementation standards.

Skills

AI governance

Risk management

Stakeholder management

Executive communication

Cloud governance

Education

Bachelor's degree in technical, risk, data or business

Tools

Microsoft Purview

Collibra

Alation

Informatica

MLflow

Job description

A large financial-services organization is building out its enterprise approach to AI governance and is seeking an experienced AI Governance Lead to help establish the framework, controls, operating model, and processes that will govern AI adoption across the organization. This is a hands‑on governance leadership opportunity for someone who understands both enterprise risk and modern AI environments. You will help move AI governance from an emerging capability into a repeatable operating model covering AI/ML, Generative AI, LLMs, RAG, intelligent automation, and advanced analytics.

RESPONSIBILITIES

• Design and operationalize enterprise AI governance frameworks, standards, controls, and processes.
• Establish governance for AI intake, inventory, risk assessment, technology review, approvals, monitoring, remediation, and reporting.
• Govern AI initiatives across the lifecycle from ideation and proof of concept through production and retirement.
• Develop controls around data quality, privacy, lineage, explainability, human oversight, auditability, access, and operational resilience.
• Partner with technology, data, business, legal, risk, compliance, cybersecurity, audit, and operations teams.
• Establish governance processes for Generative AI, LLM, RAG, and advanced-analytics solutions.
• Develop executive reporting around AI adoption, value, risk exposure, control effectiveness, and remediation.
• Translate policies and regulatory expectations into practical procedures, controls, evidence requirements, and implementation standards.

Role Requirements

• 8+ years of experience across AI governance, model risk, data governance, enterprise risk, compliance, data management, or related disciplines.
• Direct experience designing or implementing enterprise AI governance.
• Experience operationalizing governance rather than working exclusively at the policy level.
• Strong understanding of AI/ML lifecycle management and Responsible AI.
• Understanding of model risk, data risk, privacy, explainability, bias, human oversight, and operational risk.
• Experience within banking, financial services, insurance, fintech, or another highly regulated environment.
• Experience partnering across technology and control organizations.
• Strong executive communication and stakeholder-management capabilities.
• Understanding of modern AI, cloud, data, and governance environments.
• Bachelor s degree in a relevant technical, risk, data, or business discipline.

PREFERRED EXPERIENCE

• Banking regulatory experience including SR 11-7, BCBS 239, CCAR, CECL, AML/BSA, or related standards.
• Experience governing Generative AI, LLM, and RAG solutions.
• Familiarity with Microsoft Purview, Collibra, Alation, Informatica, MLflow, model registries, or AI monitoring platforms.
• Mandarin speaking ability.
• Relevant data, governance, risk, or AI certifications.