AI Governance Lead

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

Job summary

TalentOla is seeking an AI Governance Lead to define and implement the governance lifecycle for AI initiatives. You will author policies, drive cross-functional alignment across AI Engineering, Model Risk, Compliance, Legal, and business leads, and map industry guidance to practical controls within our Azure AI stack.

You will lead the creation of processes for intake, risk tiering, approval, monitoring, and decommission, ensuring robust governance for GenAI deployments in a regulated banking

Qualifications

• SR 11-7 Model Risk Management - deep, applied knowledge including GenAI use cases.
• Policy and process writing for both technical and executive audiences
• Stakeholder alignment experience across risk, compliance, legal, and technology at a bank
• 7+ yrs in model governance, risk management, or tech compliance at a regulated institution
• Enough AI/ML fluency to challenge engineers without being an ML practitioner

Responsibilities

• Define M&T's AI governance lifecycle from scratch: intake, risk tiering, approval, monitoring, decommission
• Author the documentation - AI Use Policy, MRM standards, acceptable-use guidelines, escalation playbooks
• Drive alignment across AI Engineering, Model Risk, Compliance, Legal, and business unit leads
• Map SR 11-7, OCC/FDIC AI guidance, and NIST AI RMF to practical engineering controls
• Partner with platform engineers to embed controls (audit logs, content filters, explainability) into the Azure AI stack

Skills

SR 11-7

Policy writing

Stakeholder alignment

Model governance

AI/ML fluency

Job description

AI Governance Lead 1 Role | Start: Immediate

What They'll Do

• Define M&T's AI governance lifecycle from scratch: intake, risk tiering, approval, monitoring, decommission
• Author the documentation - AI Use Policy, MRM standards, acceptable-use guidelines, escalation playbooks
• Drive alignment across AI Engineering, Model Risk, Compliance, Legal, and business unit leads
• Map SR 11-7, OCC/FDIC AI guidance, and NIST AI RMF to practical engineering controls
• Partner with platform engineers to embed controls (audit logs, content filters, explainability) into the Azure AI stack

Must-Have Skills

• SR 11-7 Model Risk Management - deep, applied knowledge including GenAI use cases
• Policy and process writing for both technical and executive audiences
• Stakeholder alignment experience across risk, compliance, legal, and technology at a bank
• 7+ yrs in model governance, risk management, or tech compliance at a regulated institution
• Enough AI/ML fluency to challenge engineers without being an ML practitioner