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Sr. Product Manager, Databricks AI

Databricks

San Francisco, CAFull time5-10 yearsNot Disclosed

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Job Description

RDQ127R47

At Databricks, we are passionate about enabling every organization to harness the power of data and AI. Our mission is to build the best platform for developing, deploying, and operating AI applications at scale—so customers can use intelligence to transform their businesses.

More About The Team

The Databricks AI team is at the forefront of shaping how enterprises leverage AI. Our mission is to create foundational capabilities that empower customers to develop agents and models, orchestrate complex workflows, and seamlessly integrate AI into their data and applications. The AI industry is evolving rapidly, and our work demands both first-principles thinking and the agility to adapt to these changes. We are not just building features; we are fundamentally transforming how the world builds with AI.

The Impact You Will Have

  • Shape the future of enterprise AI: Define and drive the vision for how Databricks helps customers harness generative AI, agents, and new workloads that don’t exist yet
  • Turn breakthroughs into products: Partner with world-class engineering and research teams to transform cutting-edge AI advancements into practical, trusted tools for millions of users.
  • Expand what’s possible for customers: Engage directly with data and AI leaders to uncover new use cases — then design products that make the once-impossible accessible and repeatable.
  • Be the voice of vision and execution: From concept to launch, you will inspire the roadmap, guide engineering, and tell the story of how Databricks AI is changing what customers can achieve.
  • Build for scale and longevity: Define the strategy and principles that will guide Databricks AI for years, even as the industry evolves at unprecedented speed.

What We Look For

  • 5+ years of product management or equivalent experience, preferably with enterprise SaaS or developer platforms.
  • Strong technical background in computer science, AI/ML, or related engineering fields (educational or professional).
  • Proven ability to partner with senior engineers and research leaders, going deep on technical concepts while maintaining clarity on customer value.
  • Track record of bringing products from vision to launch in fast-moving, competitive spaces.
  • Strong analytical skills—comfortable working with SQL, product usage data, and operational dashboards.
  • Excellent communication and storytelling skills to engage diverse stakeholders (customers, engineering, go-to-market).
  • Bonus: exposure to building AI/ML or generative AI–powered products.

Pay Range Transparency

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 here.

Zone 1 Pay Range

$156,600—$215,250 USD

About Databricks

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 Twitter, LinkedIn and Facebook.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

About The Company

Databricks

Databricks is the Data and AI company. More than 10,000 organizations worldwide — including Block, Comcast, Condé Nast, Rivian, Shell and over 60% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to take control of their data and put it to work with 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. --- Databricks applicants Please apply through our official Careers page at databricks.com/company/careers. All official communication from Databricks will come from email addresses ending with @databricks.com or @goodtime.io (our meeting tool).

Company Size5000-10000
HeadquartersSan Francisco, CA
IndustrySoftware Development
TypePrivately Held
SpecialitiesApache Spark, Apache Spark Training, Cloud Computing, Big Data, Data Science, Delta Lake, Data Lakehouse, MLflow, Machine Learning, Data Engineering, Data Warehousing, Data Streaming, Open Source, Generative AI, Artificial Intelligence, Data Intelligence, Data Management, Data Goverance, Generative AI, and AI/ML Ops

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