Elastic - Principal Product Manager II, AI/Vectors
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. • 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. • 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 people is the right thing to do. • Competitive pay based on the work you do here and not your previous salary • Health coverage for you and your family in many locations • Ability to craft your calendar with flexible locations and schedules for many roles • Generous number of vacation days each year • Increase your impact - 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 you love • Embracing parenthood with a minimum of 16 weeks of parental leave
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. 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.
Apply in one click
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT