Senior Developer Relations Engineer, AI Foundation and Security

Google Google · Big Tech · Sunnyvale, CA +4

Senior Developer Relations Engineer for AI Foundation and Security at Google. This role involves building production-ready AI applications, integrating AI into secure workflows, demonstrating deployment at scale, and creating content to drive developer adoption of Google Cloud and Google AI. The role also involves providing feedback on AI features and influencing product roadmaps.

What you'd actually do

  1. Design, build, and maintain production-grade AI applications and agentic workflows to demonstrate deployment at scale.
  2. Create engaging technical demos, blogs, and videos that demystify complex AI developer problems and drive share of voice.
  3. Be able to dogfood AI features and provide actionable feedback to developer teams to resolve developer friction and influence product roadmaps.
  4. Manage developer programs, workshops, and hackathons to foster a vibrant community for AI solutions on Google Cloud.
  5. Develop comprehensive resources, including sample code and tutorials, while representing Google at industry events and conferences.

Skills

Required

  • Integrating or building production-grade generative AI, large language models (LLMs), or multi-agent workflows into applications
  • Producing engaging developer content (e.g., blogs, short-form videos, podcasts, live streams)
  • Technical role experience (e.g., software engineering, solutions consultant)
  • Computer Science degree or equivalent practical experience

Nice to have

  • Designing production-grade AI apps and agentic workflows to showcase secure, scalable deployments
  • Leading workshops and hackathons to foster a vibrant AI solution community on Google Cloud
  • Leading industry events while developing sample code and tutorials for strategic enablement
  • Creating technical demos and content to demystify complex AI problems and drive developer adoption
  • Leading pre-launch testing of AI features to provide actionable engineering feedback and resolve developer friction

What the JD emphasized

  • production-grade AI applications
  • agentic workflows
  • deployment at scale
  • secure AI workloads
  • developer adoption

Other signals

  • Build production-ready AI applications
  • Integrate AI into secure product workflows
  • Demonstrate deployment at scale
  • Create engaging content, demos, blogs, and videos
  • Drive developer adoption to Google Cloud and Google AI