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Principal Product Manager II, AI/Vectors - Elasticsearch

Elastic· Enterprise Search - Product Management
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Ireland€130.9k - €207.1kfull-timePosted 5d ago

About the role

Senior product leader responsible for strategy and roadmap of Elastic's embedding/reranking, vector database, and related AI/vector retrieval capabilities, with emphasis on vector indexing, hybrid retrieval, and developer-facing APIs/SDKs.

Responsibilities

  • Conduct market research to uncover emerging trends in search/vector databases and SOTA model research for unstructured data
  • Evaluate competitive landscape and develop user personas to guide feature decisions
  • Collaborate with cross-functional teams to align product strategy with business goals and prioritize features based on feedback and market demands
  • Establish long-term product goals and milestones for vector use cases and document AI/unstructured data management; prioritize features based on user feedback and feasibility; allocate resources and coordinate with engineering to validate roadmap assumptions
  • Own the vision, strategy, and multi-quarter roadmap for Elastic's vector database and core search use cases from indexing internals to developer-facing APIs/SDKs
  • Partner with engineering and applied research to discuss trade-offs; define metrics (recall, latency, index size, ingestion throughput, total cost of ownership) and advance Elastic AI/Vector competitiveness across deployments
  • Define unified strategy/roadmap across embedding/reranking models, vector indexing, semantic ingestion, model lifecycle, and end-to-end retrieval quality
  • Manage operating cadence to align research, cloud, and engineering teams and address cross-domain trade-offs

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or related field
  • Master's degree in a relevant discipline preferred
  • 8+ years in product management with significant time on technical infrastructure, databases, search, or ML/AI platforms
  • Working knowledge of vector search fundamentals (embeddings, ANN indexing, similarity metrics, recall vs latency) and hybrid retrieval
  • Working knowledge of generative models, model fine-tuning, model capabilities, and document processing for large corpora
  • Ability to collaborate with engineers and ship developer- or infrastructure-facing products adopted at scale

Skills

Required:Vector search fundamentalsHybrid retrievalGenerative models and fine-tuning

Benefits

  • Competitive pay
  • Health coverage for you and family in many locations
  • Flexible locations and schedules for many roles
  • Generous vacation days
  • Company match for charitable donations up to $2000
  • Up to 40 hours/year for volunteer projects
  • Parental leave minimum of 16 weeks
Last updated Oct 22, 2026. Interested? Apply on the company site.
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