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Sr. Manager, Engineering - Vector Search

Databricks
San Francisco, United Statesfull_timeVerifiedPosted 15 Apr 2025
💰 $300,000/yr($222,000/yr$300,000/yr)

About the role

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At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

Our Vector Search technology is at the heart of this mission, enabling developers to significantly enhance the accuracy of Retrieval Augmented Generation (RAG) and other generative AI applications. By facilitating similarity searches across a wide array of unstructured documents—including PDFs, Office documents, and Wikis—Vector Search has quickly become our fastest-growing product. This surge is fueled by the escalating demand for Generative AI capabilities among our customers. As the Engineering Team Lead for Vector Search, you'll spearhead the development of an affordable Vector Search product to power AI applications designed for ease of use, scalability, and unparalleled performance. 

The key responsibilities include:

  • Leading a team of talented software engineers to build the next-generation multi-tenanted, cloud native Vector Search service
  • Growing the team by hiring strong engineering talent
  • Leading and participating in technical, product, and design discussions relating to vector databases
  • Managing and operating a highly-available service in the cloud
  • Growing leaders on the team by providing coaching, mentorship, and growth opportunities
  • Playing a key role in defining the product and engineering roadmap for the team
  • Partnering with other engineering and product leaders on planning, prioritization and staffing
  • Creating a culture of excellence on the team while leading with empathy

What we look for:

  • 5+ years experience working in, database systems, search, or AI/ML systems
  • Experience building highly-available cloud services
  • Building, growing, and managing high performance teams
  • Experience in defining and meeting SLOs for highly-available systems
  • Ability to attract and hire engineers who meet the Databricks hiring standards
  • Knowledge of database internals (highly Preferred)
  • BS in Computer Science (Masters or PhD Preferred)

 

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base 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 utilizes 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.

 

Local Pay Range$222,000$300,000 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 TwitterLinkedIn 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, please visit https://www.mybenefitsnow.com/databricks

Our Commitment to Diversity and Inclusion

At Databri

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Databricks

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