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Principal Product Marketing Manager, AI Governance

Databricks

Job at a glance

Category
AI Governance
Work arrangement
On-site
Location
San Francisco, California
Salary range
$193,500
Posted
Aug 11, 2026
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Databricks is hiring a Principal Product Marketing Manager, AI Governance in San Francisco, California. This is a AI Governance job in the governance, risk, and compliance field, with a posted range of $193,500. Review the full details below and apply directly with Databricks.

1 MKTQ127R8 1 While candidates in the listed locations are encouraged for this role, candidates in other locations will be considered. Agentic AI has taken the world by storm and Databricks is proud to be a leader in this space. With a data-centric approach to AI, Databricks enables customers to build high-quality AI agents and applications with enterprise-grade governance, security, and observability. In this role, you will own product marketing for Databricks AI Governance portfolio, including Unity AI Gateway. Reporting to the Senior Director of Product Marketing, you’ll define and execute marketing strategies that drive trusted AI adoption, enable sales and partners, generate pipeline for AI products, and drive developer adoption of AI. Partnering closely with product, sales, and marketing teams, you’ll translate product innovation into clear market narratives around AI governance (e.g., access control, monitoring, policy enforcement), compelling customer content, targeted campaigns, and impactful product launches. The impact you will have: Own the marketing strategy and planning for AI governance products Build and land collateral for key channels across sales, partner, and demand generation, including content campaigns and events that highlight AI governance, compliance, and observability capabilities Create an always-on go-to-market plan and pilot new programs with a strong focus on winning AI governance mindshare, driving pipeline, and adoption of governed AI usage Build a strong and collaborative partnership with product and engineering teams to launch new products Increase global reach by working with field marketing, industry, events, and partner organizations to help scale the business globally Build trust with customers and share their agentic AI customer stories, emphasizing governance, risk mitigation, and production readiness What we look for: 8+ years of technical product marketing experience in an enterprise software company Experience with AI/ machine learning technologies Strong understanding of AI, security, and governance decision makers and builders (developers, ML engineers, platform teams), and experience building content around governed AI platforms and policy-driven controls Portfolio of impactful marketing content, sales enablement materials and always-on GTM Experience presenting at conferences and customer engagements, including topics related to AI governance, risk, and enterprise adoption Preferred BS in Computer Science or

Full responsibilities and requirements are on Databricks's application page.

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Location and market context

This job is based in San Francisco, California on-site. Local candidates benefit from being close to Databricks's teams and regional hiring market. Confirm the exact in-office expectation and any relocation support with the employer.

About AI governance jobs

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. Jobs 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 job

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 Databricks 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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