Synced from Greenhouse · Jul 1

Product Manager, AI

DatabricksSeattle, WashingtonPosted Jul 1, 2026
AI Product ManagerSenior
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Mirrored from Databricks's own Greenhouse careers system · refreshed hourly

$149k–$205k
Compensation
867
Other open Databricks roles
Jul 1
Posted
Greenhouse
Applicant system
Job descriptionReq 8136204002

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 2 Pay Range
$148,800$204,525 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

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.

View original posting on Greenhouse

What applying to Databricks usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Databricks can generally expect a structured process typical of this ATS. This commonly begins with an online application and resume screen, followed by a recruiter conversation to discuss background and role fit. Depending on the position, candidates may encounter technical assessments, take-home exercises, or case studies, particularly for engineering, data, and analytical roles. The process may include multiple stages such as hiring manager conversations, panel discussions, and team or cross-functional interviews. Response times vary and communication is typically managed through the greenhouse platform, including scheduling and status updates. Candidates should prepare to discuss relevant experience, technical skills, and role-specific scenarios, as greenhouse-based processes commonly emphasize structured evaluation criteria across candidates to support consistent, comparative hiring decisions throughout the pipeline.

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Product Manager, AI
Databricks · Seattle, Washington
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