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Databricks

Software Engineer, Web Products

Mountain View, CaliforniaFrom $187.5kmidAdded today

About this role

Join Databricks' Web Engineering team to build production-quality public-facing web experiences across databricks.com and related properties using an AI-native platform and development lifecycle. This role emphasizes shipping scalable web systems while adopting AI-assisted tools for code generation, testing, and deployment.

What you'll do

  • Build and deploy web experiences across databricks.com landing pages, blogs, hubs, and event properties
  • Implement components and page systems using a shared design system to reduce maintenance overhead
  • Work within an AI-native SDLC where agents assist with code generation, testing, and deployment
  • Optimize web surfaces for AI-driven search and discovery systems
  • Participate in code reviews and establish rigorous AI-native engineering practices
  • Integrate with content management systems and maintain unified architectural foundations

What they're looking for

  • Full-stack web development with production shipping experience
  • Component architecture and modern rendering strategies
  • Build systems and deployment pipelines
  • Content Management Systems (Drupal, Contentful, or similar)
  • AI-native development tools and practices
  • Headless CMS architectures
  • Edge delivery and modern frontend frameworks
  • Code review and collaborative engineering
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Databricks

Databricks builds a unified data and AI platform that combines database systems, distributed computing, and generative AI capabilities across multi-cloud infrastructure. The company is hiring software engineers, applied AI engineers, and web engineers to develop core database engines, ML/AI features, inference systems, and user-facing products.

Website
databricks.com
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Likely interview questions

  • Describe a production web system you shipped from conception to deployment—what was your role and what technical challenges did you solve?
  • How have you used AI-assisted development tools in your workflow, and how would you integrate them into a daily engineering practice?
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