AI Governance Lead

Role SummaryOwn 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 ResponsibilitiesGovernance Framework DesignAuthor and maintain AI governance standards, policies, and procedures covering the full lifecycle of AI use cases and modelsDesign the governance roadmap organized into intake, classification, value assessment, and control design stagesDefine risk tiers and controls proportional to use case risk (e.g., low/medium/high risk classification tied to required controls)Use Case GovernanceBuild the intake process for new AI use cases: how requests enter the pipeline, what information is captured, who reviews themEstablish classification criteria (risk level, data sensitivity, regulatory exposure, business criticality)Design value assessment methodology to prioritize use cases against cost, risk, and business impactDefine control requirements per classification tier (documentation, testing, sign-off, monitoring)Model GovernanceEstablish model risk management practices: validation, documentation, versioning, approval gatesDefine requirements for model cards, testing evidence, bias/fairness checks, and performance monitoringSet standards for third-party and open-source model vettingTarget State & Team BuildDefine the target state for AI governance: what "good" looks like, what the organization should expect from the functionDesign the governance team structure, roles, and operating modelSet RACI across governance, engineering, legal, risk, and business stakeholdersImplementation & MonitoringBuild a phased implementation plan with milestones and ownersPrioritize governance rollout in sequence with engineering platform and architecture deliveryEstablish monitoring and reporting: KPIs, compliance tracking, exception handling, escalation pathsRun periodic reviews of the governance program's effectiveness and adjust as neededRequired QualificationsCombined minimum of 10 years' higher education and/or operational/business analytics/systems development experienceDemonstrated experience building a governance framework or program from the ground up in a large or complex organizationWorking knowledge of model risk management practices (e.g., SR 11-7 or equivalent) and how they extend to AI/ML systemsExperience designing intake, classification, and risk assessment processes for technology or data initiativesExperience working cross-functionally with engineering, legal, compliance, and business teamsStrong written communication skills; able to produce policy documents, standards, and executive-level reportingBachelor's degree in a relevant field (risk, business, computer science, law, or similar); advanced degree a plus but not required in place of experiencePreferred QualificationsDirect experience with AI-specific regulatory frameworks (EU AI Act, NIST AI RMF, ISO/IEC 42001) and applying them practicallyPrior experience standing up or scaling a governance team, including hiring and role designFamiliarity with MLOps and model deployment pipelines, enough to design controls that don't bottleneck engineeringExperience 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 credentialsExperience in a regulated industry (financial services, healthcare, insurance)Skills RequiredPolicy and standards writingRisk classification and control designStakeholder management across technical and non-technical audiencesProgram/project management (roadmap building, milestone tracking, prioritization)Working knowledge of ML lifecycle and model development practicesData literacy: able to read model documentation, validation reports, and technical risk assessmentsFacilitation and negotiation, particularly balancing governance rigor against engineering velocity#LI-JB3M&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.LocationBuffalo, New York, United States of AmericaSummaryLocation: Buffalo, NYType: Full time