# Senior Manager - Data & AI Governance at Mercury

- Company: Mercury
- What the company does: Everything you do with money. All in one place. Apply in 10 minutes for business banking that transforms how you operate. Backed by Sequoia, a16z and 500 Global.
- Company website: https://mercury.com/
- Type: Startups (AI role)
- Level: Senior
- Location: San Francisco, CA, New York, NY, Portland, OR, or Remote within United States
- Work setup: Remote
- Posted: 2026-08-13
- Apply by: 2026-10-08
- Apply: https://job-boards.greenhouse.io/mercury/jobs/6142625004
- Page: https://www.1752.vc/careers/jobs/mercury-senior-manager-data-and-ai-governance/

## About the role

This role will work closely with the Model Risk Management and Information Security teams while maintaining a distinct mandate: Data & AI Governance will establish enterprise governance and responsible-use standards, while Model Risk Management will retain responsibility for model inventory, tiering, validation, and model-risk oversight. Our target new hire base salary ranges for this role are the following :

## What they're looking for

- 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, training and inference data, explainability, bias, performance monitoring, and human oversight
- Experience developing practical, risk-based policies and governance processes that can operate effectively 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

Tags: Enterprise Risk