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Principal Product Manager II, AI/Vectors Elasticsearch

Elastic· Enterprise Search - Product Management
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Hybrid (United Kingdom)full-timePosted 5d ago

About the role

Senior product management role owning strategy and roadmap for Elastic's embedding/reranking, vector database, and related AI/vector capabilities, including vector indexing, hybrid retrieval, and developer APIs/SDKs.

Responsibilities

  • Conduct market research to uncover emerging trends in search/vector databases and SOTA model research for unstructured data, collaborating with the model team.
  • Evaluate the competitive landscape to enhance product positioning and develop user personas guiding feature decisions.
  • Collaborate with cross-functional teams to align product strategy with business goals and prioritize features based on customer feedback and market demands.
  • Establish long-term product goals and milestones for vector use cases and document AI/unstructured data management to drive development; prioritize features and allocate resources to ensure timely updates; 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 and SDKs.
  • Partner with engineering and applied research on trade-offs; define and defend key metrics (recall, latency, index size, ingestion throughput, total cost of ownership); advance Elastic AI and Vector products across deployments.
  • Define a unified strategy and roadmap across embedding/reranking models, vector indexing/semantic ingestion, model lifecycle, and end-to-end retrieval quality.
  • Manage the operating cadence to align research, cloud, and engineering teams; address trade-offs where model and index decisions intersect.

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
  • Experience shipping developer- or infrastructure-facing products adopted at scale
  • Ability to engage technically with engineers on vector/search topics

Skills

Required:Vector search fundamentalsHybrid retrievalGenerative models and fine-tuning

Benefits

  • Competitive pay based on the work you do here and not your previous salary
  • Health coverage for you and your family in many locations
  • Flexible locations and schedules for many roles
  • Generous vacation days
  • Matching donations up to $2000 or local currency equivalent
  • Up to 40 hours per year for volunteer projects
  • Minimum of 16 weeks of parental leave
Last updated Oct 22, 2026. Interested? Apply on the company site.
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