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Elastic

Principal Product Manager II, AI/Vectors

RemoteUnited States only
Published
Role
Product
Experience
Principal
Employment
Full-time
$199.7k–$315.9k/yr
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Open to US only. Set where you work from to check your eligibility.

No BS summary

Principal Product Manager owning the strategy and roadmap for Elastic's vector search capabilities (embedding/reranking, vector database, hybrid retrieval). Needs 8+ years of product management on technical infrastructure, databases, search, or ML/AI platforms, solid hands-on knowledge of vector search fundamentals (embeddings, ANN indexing, similarity metrics, hybrid retrieval), and a track record of shipping developer/infrastructure-facing products that were adopted at scale.

Core skills

Vector searchEmbeddingsANN indexing

Required skills

Similarity metricsHybrid retrievalGenerative/AI modelsModel fine-tuningDocument processing

What you'll do

  • Conduct market research to uncover work trends in search/vector databases, new model research topics across the LLM landscape
  • Evaluate the competitive landscape to enhance product positioning and develop user personas
  • Coordinate collaboration with cross-functional teams on prioritizing product features, driven by user feedback and market demands
  • Establish long-term product goals and milestones for vector use cases, document AI and unstructured data management
  • Prioritize features based on user feedback and technical feasibility; allocate resources to ensure timely updates
  • Communicate updates and expectations clearly to stakeholders and executives
  • 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 deeply with engineering and applied research on trade-offs, being a credible technical coworker
  • Define and advocate for headline metrics: recall, latency, rarity, ingestion throughput, total cost of ownership
  • Advance competitiveness of Elastic AI and Vector products across all deployment models — Serverless and Self-managed
  • Build 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 on shared metrics and priorities

What they require

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

Benefits

  • Cash compensation plus eligibility to participate in Elastic's stock program
  • Company-matched 401(k) with dollar-for-dollar matching up to 6% of eligible earnings
  • Competitive pay based on the work you do, not your previous salary
  • Health coverage for you and your family in many locations
  • Flexible locations and schedules for many roles
  • Generous number of vacation days each year
  • Match up to $2000 (or local currency equivalent) for financial donations and community service
  • Up to 40 hours each year for volunteer projects
  • Minimum 16 weeks of parental leave

distributed, scalable, and highly available real-time search platform with a RESTful API

TechnologyEnterpriseelastic.co/elasticsearch/

What people say about this company

3.8/ 5

$199.7k–$315.9k/yr