Principal Product Manager, AI Agents - Search

Elastic Elastic · Enterprise · United States · 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, and working with data science and engineering on benchmarking and evaluations.

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

  • Product management for technical, cloud infrastructure, or platform products
  • Leading sophisticated, data-intensive products from inception through launch and iterative growth
  • Deep technical understanding of the AI/ML landscape, including LLMs, RAG architectures, vector databases, and context engineering
  • Working closely with engineers and data scientists to solve intricate technical challenges
  • Leadership and Influence across a matrixed organization
  • Communication Excellence (spoken and written)
  • Customer Obsession

Nice to have

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

What the JD emphasized

  • 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 layer for agents
  • build, manage, and scale context for AI agents
  • RAG architectures
  • vector databases