AI Governance Manager
United States · Remote · Permanent
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What the market looks like
Over the last six months, we've tracked 600+ management-level postings in AI governance across the US, with concentration in California, New York, and Texas. Financial services, professional services, and technology firms dominate hiring, reflecting heightened regulatory and compliance pressure around AI deployment. Compensation for this cohort ranges from $180K to $320K annually. The strongest candidates bring hands-on experience translating AI risk frameworks into operational policy, cross-functional credibility with product and legal teams, and a pragmatic balance between governance rigor and organizational velocity.
Job responsibilities
Own the design and evolution of AI governance frameworks, policies, and controls—from model transparency and bias assessment through data lineage and monitoring protocols
Partner with product, engineering, and data teams to embed governance into development workflows, ensuring compliance with internal standards and emerging regulatory requirements
Lead cross-functional governance working groups, translating requirements from legal, risk, and compliance into practical implementation roadmaps
Build and maintain an AI model inventory and audit trail; establish baselines for model performance, drift, and fairness across the organization
Develop and deliver governance training and best-practice guidance to engineers, data scientists, and product managers
Monitor regulatory landscape shifts and competitive governance practices; recommend policy updates in response to new guidance or organizational changes
Establish metrics and dashboards to track governance maturity, policy adherence, and audit readiness
Candidate requirements
5+ years in AI governance, compliance, risk management, or audit roles—preferably with direct experience shaping AI/ML policy and controls in regulated environments
Demonstrated ability to translate technical AI/ML concepts into clear governance frameworks and communication for non-technical stakeholders
Track record building and leading governance or compliance programs; comfortable influencing without pure authority in cross-functional settings
Working familiarity with AI risk areas (model bias, transparency, data quality, security, drift) and emerging standards (NIST AI RMF, EU AI Act, industry-specific guidance)
Strong project and program management skills; ability to balance governance ambition with organizational feasibility and speed
Clear written and verbal communication; experience presenting governance updates and risk assessments to senior leadership