Staff Software Engineer, Full Stack - Gen AI

Scale AI Scale AI · Data AI · San Francisco, CA · Gen AI Engineering

Staff Fullstack Engineer & Architect for Generative AI Data Engine, focusing on platform architecture, scalability, and integration with LLMs. The role involves deploying into critical product initiatives, leading architectural overhauls, and working across backend, frontend, and ML systems to support AI data operations.

What you'd actually do

  1. Deploy flexibly into critical, fast-moving product initiatives across the CB organization
  2. Lead the architectural overhaul of our platform infrastructure, making it highly sustainable, robust, and optimized for deep integration with LLMs and foundation models.
  3. Lead architecture decisions for scalability, reliability, and performance
  4. Mentor and uplevel engineers across the team
  5. Partner with product and leadership to shape roadmap and priorities

Skills

Required

  • 7+ years of full-time engineering experience
  • proven track record of operating as a Tech Lead, Architect, or Principal Engineer
  • Track record of shipping high-quality products and features at scale
  • Proficient in Javascript/Typescript
  • Proficient in SQL
  • Experience with Kubernetes
  • Experience with major cloud providers (AWS, Azure, GCP)

Nice to have

  • Experience tinkering with or productizing LLMs
  • Experience tinkering with vector databases
  • Experience tinkering with the other latest AI technologies

What the JD emphasized

  • Staff Fullstack Engineer & Architect
  • architectural overhaul
  • deep integration with LLMs
  • ML systems

Other signals

  • powers the world’s most advanced LLMs and generative models
  • high-impact datasets that push the boundaries of LLM capabilities
  • optimize contributor onboarding and incentives
  • safeguarding data integrity through advanced trust, safety, and security measures
  • work at the intersection of ML, operations, and analytics
  • architectural overhaul of our platform infrastructure
  • optimized for deep integration with LLMs and foundation models
  • Work across backend, frontend, and ML systems