Product Manager, Data Indexing, AI Foundations

Google Google · Big Tech · San Jose, CA +1

Product Manager responsible for defining the strategy and roadmap for a planet-scale data processing platform that evolves multimodal pipelines to power Google's core AI models (Gemini) and next-generation agents. The role focuses on acquiring, processing, and indexing high-quality multimodal data to fuel LLM training and enable agentic applications.

What you'd actually do

  1. Gain a deep understanding of the evolving data requirements for Google Search, Large Language Models (LLMs), RAG applications, and other information retrieval clients to inform the native multimodal data pipelines strategy using AI-based signal processing technologies.
  2. Build and manage an actionable roadmap that accelerates model development by Google DeepMind researchers, AI adoption by Google’s marquee businesses.
  3. Take technical products from conception to launch by driving execution to achieve desired business impact.
  4. Partner across the Product Management, Engineering, Program, Research and Customer Engagement partners to align priorities, influence decisions and remove execution blockers.

Skills

Required

  • 5 years of experience in product management, or a related technical role.
  • 2 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc.).
  • Experience integrating generative AI tools or LLM interfaces into workflows.
  • Experience building and scaling developer platforms, developer-facing APIs/SDKs, or general backend infrastructure (e.g. for search or AI applications).

Nice to have

  • Master's degree in a technology or business related field.
  • 2 years of experience in software development or engineering.
  • 1 year of experience in technical leadership.
  • Experience with data processing using Large Language Models (LLMs), Model Development, Model Training, Retrieval-Augmented Generation (RAG).
  • Exceptional cross-functional leadership skills, with the ability to influence without authority across engineering, research, and product areas.
  • Excellent problem solving skills, with the ability to define user journeys and success metrics.

What the JD emphasized

  • radically innovating how we acquire, process, and index fresh, high-quality multimodal data
  • Raw, web-scale crawled data must become trusted, structured data to fuel Large Language Model (LLM) training and enable agentic applications to retrieve and reason over context.
  • evolve multimodal pipelines to power Google's core AI models, Gemini, and next-generation agents
  • build the foundational data stack shaping the future of AI

Other signals

  • Define the strategy for our planet-scale data processing platform
  • Evolve multimodal pipelines to power Google's core AI models, Gemini, and next-generation agents
  • Build the foundational data stack shaping the future of AI