Product Manager

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Its cloud-based Search AI Platform brings together search and AI for search, security, and observability.

• Lead the strategy and roadmap for embedding and reranking, the vector database, and related capabilities.
• Conduct market research on search and vector databases and emerging models for unstructured data; work with the model team.
• Evaluate competitors, improve product positioning, and develop user personas to guide feature decisions.
• Align product strategy with business goals and prioritize features based on customer feedback and market demand.
• Set long-term goals and milestones for vector use cases, document AI, and unstructured data management; prioritize enhancements based on user feedback and technical feasibility, allocate resources, validate roadmap assumptions with engineering, and communicate updates to stakeholders and executives.
• Own the multi-quarter vision, strategy, and roadmap for the vector database and core search use cases, from indexing internals to developer-facing APIs and SDKs.
• Partner with engineering and applied research on trade-offs; define and defend metrics including recall, latency, index size, ingestion throughput, and total cost of ownership.
• Advance Elastic AI and Vector products across Serverless and Self-managed deployments.
• Define a unified strategy and roadmap for embedding and reranking models, vector indexing, semantic ingestion, model lifecycle, and end-to-end retrieval quality.
• Manage operating cadence and align shared metrics and priorities across research, cloud, and engineering teams; address trade-offs between model and index decisions.

• Bachelor's degree in Computer Science, Engineering, or a related field; a relevant master's degree is preferred.
• 8+ years of product management experience, including significant time in technical infrastructure, databases, search, or ML/AI platforms.
• Working knowledge of vector search fundamentals, including embeddings, ANN indexing, similarity metrics, recall/latency trade-offs, and hybrid retrieval.
• Working knowledge of generative models, model fine-tuning and capabilities, and document processing for large corpora.
• Track record of shipping developer- or infrastructure-facing products adopted at scale; able to engage credibly with engineers on these topics.

• The position is described as part of a distributed company. Flexible locations and schedules are available for many roles; no specific work arrangement is stated for this role.
• Base salary only; no variable compensation. Typical starting annual salary range: CAD 192,500–304,500. Eligible for Elastic's stock program and a company-matched RRSP, dollar-for-dollar up to 6% of eligible earnings.
• Benefits include health coverage for employees and family in many locations, generous vacation, up to $2,000 matched for donations and service, up to 40 volunteer hours each year, and at least 16 weeks of parental leave.
• Salary placement depends on factors including education, qualifications, certifications, experience, skills, location, performance, and business or organizational needs. Pay is based on the work done, not previous salary.
• Elastic is an equal opportunity employer committed to an inclusive culture. Applicants with disabilities may request recruiting accommodations by emailing candidate_accessibility@elastic.co; requests receive a reply within 24 business hours.
• Employment may require an export license for individuals located in or nationals of Belarus, Cuba, Iran, North Korea, Syria, or Russia, including the listed Ukrainian territories. National origin or nationality does not otherwise affect eligibility.