Skip to main content
Elastic

Principal Product Manager II, AI/Vectors

RemoteUnited States only
Published
Role
Product
Experience
Principal
Employment
Full-time
$199.7k–$315.9k/yr
Check eligibility

Open to US only. Set where you work from to check your eligibility.

No BS summary

Senior product manager to own strategy and roadmap for Elastic's embedding/reranking, vector database and vector search features. Requires 8+ years product management on technical infrastructure/databases/search or ML platforms and working knowledge of embeddings, ANN indexing, hybrid retrieval and generative models. US-based role (hiring in the United States).

Core skills

vector searchembeddingsvector databases

Required skills

ANN indexinghybrid retrievalmodel fine-tuninggenerative modelsdocument ingestion/processingAPIsSDKsvector indexing

What you'll do

  • Conduct market research to uncover emerging trends in search/vector databases and SOTA model research to manage unstructured data.
  • Evaluate the competitive landscape to enhance product positioning 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 customer feedback and market demands.
  • Establish long-term product goals and milestones for vector use cases and document AI and unstructured data management to drive development.
  • Prioritize features and enhancements based on user feedback and technical feasibility and allocate resources to ensure timely updates.
  • Coordinate with engineering teams to validate roadmap assumptions and communicate updates and expectations 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 and act as a credible technical peer.
  • Define and defend metrics such as recall, latency, index size, ingestion throughput, and total cost of ownership.
  • Advance competitiveness of Elastic AI and Vector products across deployments (Serverless and Self-managed).
  • Define a unified strategy and roadmap across embedding/reranking models and vector indexing/semantic ingestion, model lifecycle, and end-to-end retrieval quality.
  • Manage the operating cadence and align shared metrics and priorities across research, cloud, and engineering teams.
  • Address trade-offs where model and index decisions intersect.

What they require

  • 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.
  • Good working knowledge of vector search fundamentals, including embeddings, ANN indexing, similarity metrics, and trade-offs between recall and latency.
  • Working knowledge of hybrid retrieval.
  • Working knowledge of generative models, model fine tuning, model capabilities and document processing for large corpus.
  • Able to hold technical conversations with engineers and applied researchers.
  • Track record of shipping developer- or infrastructure-facing products that were adopted at scale.

Benefits

  • Eligible to participate in Elastic's stock program.
  • Company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings.
  • Health coverage for you and your family in many locations.
  • Flexible locations and schedules for many roles.
  • Generous number of vacation days each year.
  • We match up to $2000 (or local currency equivalent) for financial donations and service.
  • Up to 40 hours each year to use toward volunteer projects.
  • Minimum of 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