Principal Product Manager II, AI/Vectors - Elasticsearch

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. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We're looking for a Principal Product Manager to lead the strategy and roadmap for Elastic's embedding/reranking and vector database and related capabilities. In this senior role, you'll be the go-to expert on search/vector search, guiding the direction for technologies like vector indexing and hybrid retrieval. This position offers the chance to shape a vital part of our product, working closely with engineering and research teams to ensure that our offerings meet the needs of numerous organizations while keeping pace with the evolving landscape of AI. What You Will Be Doing • 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. Prioritize features and enhancements based on user feedback and technical feasibility. Allocate resources skillfully to ensure timely updates, while coordinating with engineering teams to validate roadmap assumptions. Communicate updates and expectations clearly to stakeholders and executives. • 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 and defend the metrics that matter: recall, latency, index size, ingestion throughput, and total cost of ownership. Advance the competitiveness of Elastic AI and Vector products across all 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. Make sure shared metrics and priorities align the research, cloud, and engineering teams. Address trade-offs where model and index decisions intersect. What You Bring • 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. • You should have good working knowledge of vector search fundamentals. This includes embeddings, ANN indexing, similarity metrics, and trade-offs between recall and latency. Additionally, you need to know about hybrid retrieval. • You should have a working knowledge of generative models, model fine tuning, model capabilities and document processing for large corpus • You don't need to be a researcher, but you should hold your own with engineers on these topics. A track record of shipping developer- or infrastructure-facing products that were adopted at scale. Compensation for this role is in the form of base salary. This role does not have a variable compensation component. The typical starting salary range for new hires in this role is listed below. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below. These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the ranges may be modified in the future. An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being. The typical starting salary range for this role is: $199,700—$315,900 USD The typical starting salary range for this role in the select locations listed above is: $239,800—$379,300 USD Additional Information - We Take Care of Our People As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do. We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our pe