Senior Staff Technical Lead, Google Ads Recommendations

Google Google · Big Tech · Mountain View, CA +1

Senior Staff Technical Lead for Google Ads Recommendations, focusing on the frontend serving infrastructure for Recommendations, Insights, and Performance Diagnostics. This role involves leading a team, driving technical strategy, architecting the frontend serving stack, and overseeing the development of next-generation AI-powered capabilities using LLMs for agentic experiences and personalized guidance to advertisers. The work directly contributes to advertiser success and business growth.

What you'd actually do

  1. Manage and mentor a team of Software Engineers and Technical Leads, fostering a culture of engineering excellence, product ownership, and continuous growth.
  2. Drive the technical strategy and end-to-end execution for the Ads Diagnostics, Insights, and Recommendations pillars, delivering features that drive significant incremental business and improve advertiser trust.
  3. Architect the long-term evolution of the frontend serving stack, transitioning from multiple isolated server binaries to a unified, scalable, and high-performance platform to unblock innovation and increase engineering velocity.
  4. Oversee the development of next-generation AI-powered capabilities, including Ads Guide and Smart Summary, leveraging Large Language Models (LLMs) to provide personalized, and actionable guidance to advertisers.
  5. Maintain accountability for system health, latency, and performance metrics, ensuring that our high-scale frontend services meet the demands of the global Google Ads ecosystem.

Skills

Required

  • front-end frameworks
  • full-stack development
  • API development
  • system design
  • software design and architecture
  • software products
  • people management
  • team leadership

Nice to have

  • Experience building and scaling AI-driven product features using Large Language Models (LLMs) to create "agentic" experiences, such as conversational assistants or automated summary tools.
  • Experience with recommendation systems, Model Context Protocol (MCP) and AI Platform technologies.
  • Proven track record of leading large-scale architectural shifts, such as the unification of disparate frontend stacks or the migration of legacy server binaries into high-performance, low-latency platforms.
  • Ability to partner with Product Management (PM), UX, and Data Science leadership to translate advertiser needs into technical roadmaps that drive measurable business impact (e.g., incremental attributable business growth).

What the JD emphasized

  • AI-powered capabilities
  • agentic experiences
  • Large Language Models (LLMs)
  • recommendation systems
  • frontend serving stack
  • high-scale frontend services

Other signals

  • AI-powered capabilities
  • LLMs
  • agentic experiences
  • recommendation systems