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Senior Manager, Data & AI Governance
Mercury is hiring for the role of Senior Manager, Data & AI Governance, San Francisco, CA (Remote). This is an AI Governance role in the governance, risk, and compliance field, with a posted range of $203,300 - $282,300. Review the full details below and apply directly with Mercury.
Mercury, a financial technology company serving business banking customers, is seeking a Data and AI Governance leader to build and spearhead an enterprise-wide governance program for data and artificial intelligence. Reporting to the Chief Risk Officer, this leader establishes practical standards for how data and AI are owned, developed, used, protected, and monitored across the organization. The role works closely with the Model Risk Management and Information Security teams while holding a distinct mandate: Data and AI Governance owns enterprise governance and responsible-use standards, while Model Risk Management retains model inventory, tiering, validation, and model-risk oversight.
The Senior Manager develops Mercury's enterprise data and AI governance frameworks, policies, standards, and operating model, and establishes clear accountability for data ownership, stewardship, quality, lineage, classification, access, retention, and appropriate use. The role creates a risk-based governance process for AI use cases across their full lifecycle, including intake, assessment, approval, implementation, monitoring, and retirement, and develops responsible-AI principles addressing transparency, explainability, fairness, privacy, security, human oversight, reliability, and regulatory compliance. It also maintains an enterprise inventory of material data assets, AI use cases, and related governance decisions.
Qualifications
- 10+ years of relevant experience in data governance, AI governance, technology risk, information governance, model risk, privacy, compliance, or a related discipline
- Demonstrated experience building or materially enhancing a data governance, AI governance, or responsible-AI program
- Strong understanding of data ownership, stewardship, quality, lineage, metadata, classification, access, retention, and lifecycle management
- Working knowledge of AI and machine-learning concepts, including generative AI, large language models, explainability, bias, performance monitoring, and human oversight
- Experience developing practical, risk-based policies and governance processes in a fast-moving technology environment
- Ability to distinguish among data governance, AI governance, model risk, information security, privacy, and compliance responsibilities while coordinating effectively across those functions
Location and market context
This role is based in San Francisco on-site. Local candidates benefit from being close to Mercury's teams and regional hiring market. Confirm the exact in-office expectation and any relocation support with the employer.
About AI governance roles
AI governance sits at the intersection of policy, risk, and engineering. Teams are standing up model inventories, use-case intake and review, risk classification, and control monitoring as regulation and board scrutiny of AI intensify. Roles like this one are typically evaluated against frameworks such as NIST AI RMF, ISO/IEC 42001, the EU AI Act, and internal model-risk and privacy practices.
How to position yourself for this AI governance role
Strong candidates emphasize experience translating policy into operational controls, working across legal, compliance, security, product, and data teams, documenting AI system risks, and supporting governance processes. In your resume and outreach, tie your experience to how Mercury would apply NIST AI RMF, ISO/IEC 42001, the EU AI Act, and internal model-risk and privacy practices, and lead with concrete outcomes rather than duties.
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