Director, Product Management - Data Intelligence Foundation

Relativity•Washington, DC

7d•$188,000 - $282,000•Remote

About The Position

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. The company has built the most trusted platform in legal data, managing petabytes of sensitive data. This foundation is being transformed into the AI platform for legal data intelligence, powered by the Relativity Intelligence Model. The Foundational Layer (Relativity's shared data platform serving all AI applications) is key to this transformation, providing structure, meaning, and retrieval capabilities for AI agents to reason over legal data at scale. The Data Intelligence Foundation engineering organization is building this layer, and this role will provide product leadership, drive adoption across Relativity's product teams, and build the Product Management discipline to own it long-term. This is a high-leverage product role, crucial for making every Relativity aiR application smarter, every agent more reliable, and every Relativity product team faster.

Requirements

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.
Ability to design an API contract, contribute to engineering scope decisions, and articulate trade-offs in a data consistency model.
Demonstrated ability to manage and build a PM team through hiring, leveling, and establishing product practice for a new domain.
Bachelor's degree in Business, Computer Science, Engineering, or Design, or comparable work experience.

Nice To Haves

Experience building at companies where the data platform is the product (e.g., Snowflake, Databricks, Elastic, MongoDB, Palantir).
Experience building for AI systems, agents, or ML pipelines as primary consumers, understanding their unique data needs.
Engineering credibility to be a peer in technical discussions with engineering leaders.
Legal domain expertise is not required, but internalizing its specific design requirements is beneficial.

Responsibilities

Owning the full PM layer across multiple engineering orgs, focusing on Files/Natives (storage primitive for legal documents, images, and native files), Ontology/Relationship (semantic layer for AI reasoning), Data Capabilities (reporting, audit, and internal data infrastructure), Knowledge/Metadata (unified materialized document layer), and Query Plane (unified retrieval pillar with hybrid retrieval capabilities).
Defining the substrate for consistent accessibility of immutable legal data across products, integrations, and AI workflows, including SLAs, access contracts, and API surfaces.
Defining Relativity's Ontology to encode meaning and relationships in legal data for AI agents.
Ensuring the platform is observable, auditable, and explainable through Data Capabilities.
Evolving the Knowledge/Metadata layer to serve AI application teams as first-class consumers.
Developing a unified retrieval pillar with standardized ingestion APIs, hybrid retrieval, managed chunking, and tiered storage.
Establishing the operating rhythm for a multi-pillar PM organization, including forum structure, planning cadence, and decision frameworks.
Owning internal Go-To-Market (GTM) strategy for the Foundational Layer, defining how internal teams discover, integrate, and derive value from platform services, and measuring adoption.
Building PM capability within a scaling organization, leveling up team members while maintaining velocity.
Influencing cross-functional teams without direct authority by demonstrating clear value, evidence, and trust.
Making directional decisions with incomplete information and updating them as required.
Internalizing the importance of defensibility, chain of custody, and auditability as first-class design requirements within the legal domain.