Product Manager, Ctm Intelligence

Google Google · Big Tech · Sunnyvale, CA +1

Product Manager for the CTM Intelligence team, focusing on building the intelligence layer for Workspace AI evolution. The role involves defining and platformizing intent detection, architecting foundational platforms for AI agents, and owning artifact understanding to trigger contextual actions. It requires partnering with Engineering and Research to solve LLM orchestration problems and influencing roadmaps for automation features.

What you'd actually do

  1. Define and platformize universal intent detection across Gmail and Chat, establishing a common vocabulary for message and artifact annotation.
  2. Architect the foundational platform layer necessary to enable sophisticated follow-on actions and autonomous AI agents.
  3. Own end-to-end artifact understanding, leading the development of classifiers to extract high-signal information (e.g., meeting suggestions) and trigger contextual actions across surfaces.
  4. Partner with Engineering and Research to solve high-ambiguity problems in LLM orchestration, ensuring intent detection is both universal and actionable.
  5. Influence cross-functional roadmaps to ensure automation features, like auto-labeling based on trip or project context, are integrated seamlessly into the user experience, this includes driving the strategic direction and road map for Workspace Automation, converging it with AI Inbox initiatives to enable complex, multi-step user actions.

Skills

Required

  • Product Management
  • Technical Product Management
  • Machine Learning
  • Natural Language Processing (NLP)
  • LLMs
  • Product Roadmaps
  • Product Strategy
  • Platform Initiatives

Nice to have

  • Platformized Services
  • Infrastructure
  • Intent Detection Systems
  • Task Management Ecosystems
  • Workflow Automation Tools
  • V1 Projects
  • Model Performance Evaluation
  • Artifact Classification
  • Agentic User Experiences
  • Communication Skills
  • Stakeholder Influence

What the JD emphasized

  • building the intelligence layer
  • Agentic AI
  • LLM orchestration
  • complex, multi-step user actions
  • building products powered by Machine Learning, Natural Language Processing (NLP), or LLMs
  • platform-level initiatives

Other signals

  • Agentic AI
  • LLM orchestration
  • Define how millions of users interact with AI
  • Redefining the future of work