About the company
Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter.
Responsibilities
- Conduct market research to uncover emerging trends in search/vector databases as well as SOTA model research in emerging areas to manage unstructured data, working alongside our model team.
- Evaluate the competitive landscape to enhance product positioning and develop user personas that guide feature decisions.
- Collaborate with cross-functional teams to align the product strategy with business goals while prioritizing features based on customer feedback and market demands.
- Establish long-term product goals and milestones for the vector use cases, document AI and unstructured data management to drive its development.
- Own the vision, strategy, and multi-quarter roadmap for Elastic's vector database as well as core search use cases, from low-level indexing internals to the developer-facing APIs and SDKs.
- Partner deeply with engineering and applied research on trade-offs, be a credible technical peer in those conversations.
- 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. Make sure shared metrics and priorities align the research, cloud, and engineering teams.
Requirements
- 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: 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.
- Track record of shipping developer- or infrastructure-facing products that were adopted at scale.
Conditions
- Compensation is in the form of base salary; no variable compensation component.
- Eligible to participate in Elastic's stock program.
- Company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings.
- Range of other benefits with a holistic emphasis on employee well-being.