AI Governance Lead

M&T Bank • Buffalo, NY • 1h ago

Role Summary

Own the design and execution of the enterprise AI governance program. Build the standards, policies, and procedures that govern how AI use cases and models move from idea to production. Structure the governance roadmap across intake, classification, value assessment, and control design. Stand up use case governance and model governance functions, define the target state for AI governance across the organization, and drive an implementation plan with clear monitoring, prioritized against engineering delivery timelines.

Key Responsibilities

Governance Framework Design

Author and maintain AI governance standards, policies, and procedures covering the full lifecycle of AI use cases and models

Design the governance roadmap organized into intake, classification, value assessment, and control design stages

Define risk tiers and controls proportional to use case risk (e.g., low/medium/high risk classification tied to required controls)

Use Case Governance

Build the intake process for new AI use cases: how requests enter the pipeline, what information is captured, who reviews them

Establish classification criteria (risk level, data sensitivity, regulatory exposure, business criticality)

Design value assessment methodology to prioritize use cases against cost, risk, and business impact

Define control requirements per classification tier (documentation, testing, sign-off, monitoring)

Model Governance

Establish model risk management practices: validation, documentation, versioning, approval gates

Define requirements for model cards, testing evidence, bias/fairness checks, and performance monitoring

Set standards for third-party and open-source model vetting

Target State & Team Build

Define the target state for AI governance: what "good" looks like, what the organization should expect from the function

Design the governance team structure, roles, and operating model

Set RACI across governance, engineering, legal, risk, and business stakeholders

Implementation & Monitoring

Build a phased implementation plan with milestones and owners

Prioritize governance rollout in sequence with engineering platform and architecture delivery

Establish monitoring and reporting: KPIs, compliance tracking, exception handling, escalation paths

Run periodic reviews of the governance program's effectiveness and adjust as needed

Required Qualifications

Combined minimum of 10 years' higher education and/or operational/business analytics/systems development experience

Demonstrated experience building a governance framework or program from the ground up in a large or complex organization

Working knowledge of model risk management practices (e.g., SR 11-7 or equivalent) and how they extend to AI/ML systems

Experience designing intake, classification, and risk assessment processes for technology or data initiatives

Experience working cross-functionally with engineering, legal, compliance, and business teams

Strong written communication skills; able to produce policy documents, standards, and executive-level reporting

Bachelor's degree in a relevant field (risk, business, computer science, law, or similar); advanced degree a plus but not required in place of experience

Preferred Qualifications

Direct experience with AI-specific regulatory frameworks (EU AI Act, NIST AI RMF, ISO/IEC 42001) and applying them practically

Prior experience standing up or scaling a governance team, including hiring and role design

Familiarity with MLOps and model deployment pipelines, enough to design controls that don't bottleneck engineering

Experience with generative AI governance specifically (prompt/data leakage risk, hallucination controls, third-party LLM vendor risk)

Certifications such as CRISC, CISA, or AI governance-specific credentials

Experience in a regulated industry (financial services, healthcare, insurance)

Skills Required

Policy and standards writing

Risk classification and control design

Stakeholder management across technical and non-technical audiences

Program/project management (roadmap building, milestone tracking, prioritization)

Working knowledge of ML lifecycle and model development practices

Data literacy: able to read model documentation, validation reports, and technical risk assessments

Facilitation and negotiation, particularly balancing governance rigor against engineering velocity

LI-JB3

M&T Bank is committed to fair, competitive, and market-informed pay for our employees. The pay range for this position is $123,600.00 - $206,000.00 Annual (USD). The successful candidate's particular combination of knowledge, skills, and experience will inform their specific compensation.

Location

Buffalo, New York, United States of America

M&T Bank Corporation is an Equal Opportunity/Affirmative Action Employer, including disabilities and veterans.

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