About this opportunity
Relativity lists this Director, Product Management - Data Intelligence Foundation opportunity in columbus, Ohio. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Remote/Hybrid
Job Overview
Relativity is a leading legal data intelligence company building AI technology that helps organizations organize data, discover the truth, and act on it with confidence. Over two decades, the company has built the most trusted platform in legal data, earning deep relationships with the world's leading law firms, corporations, and government agencies, and managing petabytes of the most sensitive data in existence. That foundation is now being turned into something larger: The AI platform for legal data intelligence. The Relativity Intelligence Model is the architecture for that transformation. At its base is the Foundational Layer (Relativity's shared data platform serving all AI applications). Five primitives give AI agents the structure, meaning, and retrieval capability they need to reason over legal data at scale: Files, Ontology, Data Capabilities, Knowledge/Metadata, and Query Plane. Relativity's Data Intelligence Foundation engineering org is building this layer. The product leadership that shapes it, drives adoption across Relativity's product teams, and builds the PM discipline to own it long-term. That's this role. The Director of Product Management, Data Intelligence Foundation is one of the highest-leverage product roles at Relativity. The Foundational Layer is what makes every Relativity aiR application smarter, every agent more reliable, and every Relativity product team faster. Getting it right matters enormously.
Job Description and Requirements
What you’ll own
The full PM layer across multiple engineering orgs
Files / Natives: The storage primitive for legal documents, images, and native files. You define the substrate that makes immutable legal data consistently accessible across every product, partner integration, and AI workflow, with the SLAs, access contracts, and API surface that teams can build on with confidence. The underlying data primitives are the foundation; the degree to which the retrieval layer (Query Plane) matches this structure determines how easily the organization can navigate between "slow data" and "fast data" use cases.
Ontology / Relationship: The semantic layer of the Relativity Intelligence Model. Ontology encodes meaning: what kinds of things exist in legal data and how they relate, so that AI agents can reason, not just query. You define what Relativity's Ontology becomes: the entities, relationships, and contracts that give every Skill and Agent a shared vocabulary for legal data.
Data Capabilities: Reporting, Audit, and internal data infrastructure. The operational backbone that makes the platform observable, auditable, and explainable. These are non-negotiable properties in legal data intelligence use cases.
Knowledge / Metadata: The core data model that every product team, customer, and integration partner works with. A unified materialized document layer, consistent across all workspaces, is the mandate. Your roadmap evolves this surface to serve AI application teams as first-class consumers alongside the users who have relied on it for years.
Query Plane: One of the most performance-sensitive and strategically important services in the product. The mandate is a unified retrieval pillar with a rich materialized document layer: standardized ingestion APIs independent of data source, hybrid retrieval (lexical + vector) with reranking, chunking as a managed capability, and tiered storage (cold/warm/hot).
Minimum qualifications
12+ years in product management; 5+ years leading platform or infrastructure PM organizations
Deep fluency with data platform primitives, including storage systems, metadata layers, knowledge graphs, query engines, or equivalent. You can design an
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Worksite address
columbus, OH, 43224, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.