Staff Ux Content Designer, Search

Google Google · Big Tech · San Francisco, CA +3

This role focuses on shaping generative AI experiences within Google Search by leading model behavior design, content strategies, and training methods. The Staff UX Content Designer will develop frameworks, rubrics, and evaluation methods to ensure high-quality, trustworthy responses, working closely with researchers, PMs, and engineers. The role emphasizes influencing response quality, building user confidence, and defining standards for a reliable search experience.

What you'd actually do

  1. Lead model behavior design efforts to shape the future of Google’s generative AI experiences.
  2. Lead innovative content strategies and model training methods, blending design thinking and editorial knowledge with data analysis and prompt engineering.
  3. Develop scalable frameworks, rubrics, and evaluation methods that ensure high-quality, trustworthy responses while building user confidence.
  4. Work in close partnership with researchers, product managers, and engineers to elevate response quality in a fast-moving, evolving environment.
  5. Define the standards and patterns that ensure Google Search remains a reliable resource for users worldwide.

Skills

Required

  • UX writing
  • content design
  • technical writing
  • writing
  • editorial
  • marketing for consumer-facing technology products
  • portfolio

Nice to have

  • interacting with executive leadership
  • cross-functional technology organization
  • generative AI
  • Large Language Models (LLMs)
  • machine learning products
  • prompt engineering
  • rubric development
  • model evaluation methods
  • trust and safety
  • fact-checking
  • quality assurance for digital information products

What the JD emphasized

  • generative AI experiences
  • model behavior design
  • model training methods
  • prompt engineering
  • evaluation methods
  • high-quality, trustworthy responses
  • user confidence
  • Google Search

Other signals

  • Generative AI experiences
  • Model behavior design
  • Model training methods
  • Prompt engineering
  • Evaluation methods
  • Trustworthy responses
  • User feedback
  • Technical insights
  • Google Search