Staff Software Engineer - AI Platform (nyc)

Databricks Databricks · Data AI · San Francisco, CA · Engineering - Pipeline

Staff Software Engineer for Databricks' AI Platform team in NYC, focusing on building new GenAI agent interfaces and end-to-end AI products from scratch in a 0-to-1 environment. Requires strong full-stack and generative AI experience, including RAG, prompt design, and production monitoring.

What you'd actually do

  1. Create novel, never-seen-before interfaces for GenAI agents that manage complex workflows while keeping the human in the loop through inspectability and transparency
  2. Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive user & business growth
  3. Lead by example with hands-on full-stack software development to create dynamic, user-centric experiences
  4. Enable mechanisms that can drive product-led growth, through seamless onboarding and sharing capabilities
  5. Define and drive the strategy for building end-to-end AI feature development by designing, building, and maintaining systems that are scalable, reliable, and performant.

Skills

Required

  • 10+ years of experience with HTML, CSS, and JavaScript
  • 10+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go)
  • Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember)
  • Proven experience building and shipping end-to-end generative AI products
  • Deep familiarity with LLMs and generative AI, including hands-on experience with techniques like retrieval-augmented generation (RAG), prompt design, evaluation, and monitoring AI quality and safety in production.

Nice to have

  • Demonstrated product mindset
  • High ownership and bias for action in 0→1 environments
  • Strong ability to collaborate across product, engineering, and design teams

What the JD emphasized

  • Proven experience building and shipping end-to-end generative AI products
  • Proven experience building and shipping end-to-end generative AI products, ideally with a significant UI/UX component
  • Deep familiarity with LLMs and generative AI, including hands-on experience with techniques like retrieval-augmented generation (RAG), prompt design, evaluation, and monitoring AI quality and safety in production.

Other signals

  • building new products from the ground up
  • 0-to-1 environment
  • building and shipping end-to-end generative AI products