Principal Product Manager, AI Agents - Search

Elastic Elastic · Enterprise · San Francisco, CA · Enterprise Search - Product Management

Principal Product Manager for Elastic Agent Builder, focusing on defining how enterprises build, manage, and scale context for AI agents. This role involves understanding customer requirements, building a roadmap for context engineering capabilities, analyzing the AI Agent market, and working with data science, engineering, and design teams. The goal is to make AI agents faster, lower cost, and more accurate by enhancing their context layer.

What you'd actually do

  1. Work directly with enterprise customers, sales teams, and solution architects to understand requirements, negotiate priorities, clarify product needs
  2. Build, socialize and align a roadmap for core context engineering capabilities built on top of Elastic powered retrieval and relevance for AI Agents
  3. Deeply understand the AI Agent market, major players, trends and how it may impact our strategy
  4. Work directly data science and engineering to build out the strategy for benchmarking and evaluations of agent capabilities
  5. Work with design to build user experiences that address gaps in how agents show and refine context as they work

Skills

Required

  • 10+ years of experience in product management or solution delivery for technical, cloud infrastructure, or platform products
  • Deep technical understanding of the AI/ML landscape, including LLMs, RAG architectures, vector databases, and context engineering
  • Ability to lead across a matrixed organization, align multiple stakeholders toward a common vision, and drive execution
  • Outstanding spoken and written communication skills
  • Customer Obsession

Nice to have

  • AI tools to help accelerate your processes and bring clarity to your decisions

What the JD emphasized

  • Extensive Experience: 10+ years of experience in product management or solution delivery for technical, cloud infrastructure, or platform products.
  • Deep technical understanding of the AI/ML landscape, including LLMs, RAG architectures, vector databases, and context engineering.
  • You are comfortable working closely with engineers and data scientists to solve intricate technical challenges.

Other signals

  • AI agents
  • context engineering
  • retrieval and relevance for AI Agents
  • agent capabilities
  • AI partners