VP, AI Governance

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What the market looks like

We've tracked 80 senior-level AI governance postings across the US in the last six months, with strongest hiring concentrated in California, New York, and Texas. Professional services, technology, and financial services firms are moving fastest to formalize governance structures as AI use scales—and they're paying accordingly, with salaries ranging from $180K to $420K depending on scope and sector. The strongest candidates bring deep experience operationalizing compliance, risk, and policy frameworks across technical and business teams; they've moved beyond advisory into building actual governance infrastructure that scales.

Job responsibilities

• Own the design and execution of AI governance frameworks—policy, risk assessment, compliance, and ethical review—across the organization

• Lead cross-functional governance committees and steering bodies; partner with legal, compliance, security, product, and engineering to embed governance into AI development workflows

• Build scalable AI risk assessment and approval processes; establish clear ownership of model monitoring, bias detection, and drift management post-deployment

• Develop and communicate AI governance standards, documentation requirements, and decision-making criteria to technical and non-technical stakeholders

• Drive alignment with external regulatory requirements—depending on sector, this may include Fair Lending, HIPAA, SOC 2, or emerging AI-specific regulations

• Establish metrics and auditing cadences to measure governance maturity, identify control gaps, and report to leadership and boards on AI risk posture

• Partner with Chief AI Officer, Chief Risk Officer, or Chief Compliance Officer to translate governance strategy into operational reality

Candidate requirements

• 10+ years in compliance, risk management, legal, or governance roles—with at least 3–5 years directly building governance, policy, or audit frameworks at scale

• Demonstrated ability to translate technical AI/ML concepts into governance requirements and risk language; fluency in both technical and business contexts

• Track record of operationalizing frameworks (not just advising on them): you've written policies, designed approval workflows, built audit checklists, and measured compliance

• Experience working cross-functionally with engineering, product, and legal teams; comfort in ambiguity and ability to lead without direct authority

• Knowledge of relevant regulatory or industry standards (financial services, healthcare, Fair Lending, data protection, or emerging AI regulation is a plus)

• Executive presence and communication skills: you can explain governance trade-offs to boards and technologists with equal clarity