AI Engineering Manager

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What the market looks like

We've tracked 700+ management-level postings in AI governance over the last six months, concentrated in Professional Services, Financial Services, Technology, and Healthcare across California, New York, and Texas. Compensation for this cohort ranges from $180,000 to $340,000 annually. The strongest candidates bring hands-on experience building or scaling AI governance frameworks—risk management, policy definition, compliance integration—paired with the ability to translate technical AI concepts for non-technical stakeholders and partner across engineering, legal, and business teams.

Job responsibilities

• Own the design and rollout of AI governance frameworks, including risk assessment, model validation, and responsible AI practices across the organization

• Partner with AI/ML engineering teams to embed governance checkpoints into model development and deployment pipelines

• Build and lead an AI governance function, including hiring, mentoring, and structuring cross-functional governance working groups

• Drive compliance and risk mitigation strategies aligned with emerging AI regulation (SEC rules, EU AI Act, industry-specific mandates)

• Develop governance policies, documentation standards, and audit protocols; communicate them clearly to technical and executive audiences

• Measure and report on governance maturity, model safety metrics, and risk exposure to the board and C-suite

• Collaborate with Legal, Compliance, and Ethics teams to integrate AI governance into broader organizational risk and governance posture

Candidate requirements

• 5+ years of experience in AI governance, model risk management, AI ethics, or closely related compliance/governance discipline

• Demonstrated success building or scaling governance functions, policies, or frameworks from the ground up or in high-growth environments

• Strong grasp of AI/ML fundamentals—model types, training data, evaluation metrics, deployment lifecycle—sufficient to review technical work and identify governance gaps

• Proven ability to influence across silos: comfort translating between technical teams, legal/compliance, and executive leadership

• Experience designing and implementing risk management or compliance programs in regulated industries (Financial Services, Healthcare, or similar)

• Familiarity with emerging AI regulation, industry standards, or responsible AI frameworks (NIST AI RMF, ISO standards, or equivalent)