First San Francisco Partners - AI Governance Lead
Requirements
• 8 to 12 years of progressive experience in enterprise data governance, model risk management, corporate governance, AI/ML lifecycle oversight, or a closely related governance, risk, or compliance discipline, with engagement or program leadership scope. • Demonstrated experience setting policy and accountability frameworks at enterprise scale, not only operating frameworks set by others. • Working knowledge of how authority, accountability, and decision rights are structured in large enterprises. • Experience defining oversight structures with first-line ownership in the business, independent risk and compliance review, and audit assurance. • Track record managing a cross-functional mix of stakeholders; governance, business, technical and functional. • Strong executive communication. Able to engage senior stakeholders, frame trade-offs, and drive decisions. • Comfort working embedded alongside an in-house client team, balancing facilitation with hands-on delivery. • Bachelor’s degree in a relevant field (Information Management, Risk, Law, Business, Public Policy, Philosophy, or similar), or equivalent professional experience. • Experience in regulated industries such as agriculture, life sciences, pharmaceuticals, financial services, or healthcare. • Direct experience building AI Governance practices, even at smaller scale or as an internal program inside a single enterprise. • Hands-on experience with the EU AI Act, ideally having translated obligations into enterprise policy rather than only interpreting them. • Working knowledge of NIST AI Risk Management Framework and ISO/IEC 42001, including how they map to internal policy. • Familiarity with generative and agentic AI risks (hallucination, prompt injection, data leakage, IP exposure, autonomous decision oversight) and how enterprises are setting policy on them. • Experience operating or facilitating a Data Management Committee, AI Governance Committee, or equivalent enterprise governance forum. • What Success Looks Like • Clear AI accountability in place. Named model and use case owners in the business, defined independent risk and compliance review, and audit assurance, all mapped to existing corporate accountability structures. • A unified AI and Data Governance operating model adopted by the client, with shared accountability, intake, policies, and metadata between the two functions. • Coordinated operation of the Data Management Committee and AI Governance Committee, with cross-cutting issues handled jointly rather than falling between the two. • Live AI use case intake and risk classification applied to both predictive and generative AI use cases. • Defined enterprise position on generative AI and agentic risks, on third-party AI, and on the conditions under which the enterprise accepts each. • A documented position on the EU AI Act, NIST AI RMF, and ISO/IEC 42001 that the client’s team can defend and maintain. • Operating documentation and capabilities the client’s team can carry forward after the engagement closes. • This role is open to independent contractors operating on a 1099 or Corp-to-Corp basis, as well as candidates seeking contract to hire. Candidates must be authorized to work in the United States. • This range is based on our market pay structures. Individual salaries are determined by a variety of factors including, but not limited to business considerations, local market conditions, internal equity and candidate qualifications, such as skills, experience and education. • Pay Transparency Notice: First San Francisco Partners will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60-1.35(c) • Pay Transparency Notice:
Responsibilities
• AI Governance: • Policy Authority for AI: Define what AI the enterprise will and will not use, on what basis, and under what conditions. Includes prohibited uses, permitted uses, and the criteria that distinguish them. Author policies where needed • Policy Authority for AI: • Decision Rights for AI: Define what decisions the enterprise is willing to delegate to AI, where humans must remain in the loop, where humans review after the fact, and where AI can act autonomously. Establish how those lines are drawn, who has authority to redraw them and how they are tracked and measured. • Decision Rights for AI: • AI Use Case Intake and Risk Classification: Establish the intake process for AI use cases, including AI impact assessments and risk classification, and match the level of oversight to the level of risk. • AI Use Case Intake and Risk Classification: • Accountability Framework: Establish who is accountable when AI acts, including model and use case owners in the business, independent risk and compliance review, and audit assurance. Map this to the client’s existing corporate accountability structures rather than building a parallel one. • Accountability Framework: • Third-Party AI Position: Define how the enterprise governs third-party and vendor AI, including procurement criteria, vendor assessment standards, contractual terms, and ongoing review.
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