Staff Product Manager, AI Platform

5+ years of experience as a Product Manager working on platform or infrastructure products, ideally in ML/AI, data, or cloud services.

You should be comfortable going deep on system architecture, writing technical specs, and engaging credibly with world-class ML engineers.

Experience with ML/AI infrastructure, data platforms, or cloud services (e.g., model training, model serving, feature stores, vector search, LLM infrastructure, ML pipelines, or similar systems).

Proven enterprise B2B product management experience with highly technical customers — you have shipped platform products, driven commercial outcomes, and worked with field teams to land enterprise deals.

Databricks is committed to fair and equitable compensation practices.

Based on the factors above, Databricks anticipates utilizing the full width of the range.

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page

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$180,000

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The AI Platform team builds the infrastructure that powers machine learning and AI at scale on Databricks. Our products span the full ML lifecycle — from feature engineering and model training to model serving and monitoring — enabling data and AI teams to build, deploy, and operate production ML systems with confidence. We work across some of the most technically demanding areas in the platform, including recommendation systems, real-time inference, large-scale distributed training, LLM infrastructure, vector search, and feature stores.

Our mission is to make it radically easier for enterprises to put AI into production. We do this by providing a unified, governed, and performant AI platform that integrates deeply with the Databricks Data Intelligence Platform — connecting MLflow, Unity Catalog, Model Serving, Vector Search, Feature Engineering, LLM, and Agent infrastructure into a cohesive experience. You will join a team that ships products used by thousands of the world's most sophisticated data and AI organizations.

You will drive the vision and roadmap for AI platform product areas and define how customers build, train, deploy, and monitor AI and ML systems on Databricks. You will collaborate across engineering teams to deliver an integrated and powerful path from experimentation to production.

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on

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