Director, Product Management - Data Intelligence Foundation
Relativity · Virginia, United States · 1 mo ago
RemoteRemoteMarketing$188k–$282k/yrFull-time
Job Description
The Director of Product Management, Data Intelligence Foundation is responsible for owning the full product management layer across multiple engineering orgs, including Files/Natives, Ontology/Relationship, Data Capabilities, Knowledge/Metadata, and Query Plane. Key responsibilities include defining the substrate for legal data accessibility, shaping the ontology to encode legal data meaning, managing data capabilities for observability, auditability, and explainability, evolving the knowledge/metadata layer for AI application teams, and ensuring the query plane is a high-performance, strategic service.
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
- Experience building at companies where the data platform is the product, not a supporting system (e.g., Snowflake, Databricks, Elastic, MongoDB, Palantir)
- 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
- Experience building for AI systems, agents, or ML pipelines as primary consumers
Qualifications
- Minimum Qualifications: 12+ years in product management; 5+ years leading platform or infrastructure PM organizations; deep fluency with data platform primitives; demonstrated ability to manage and build a PM team; Bachelor's degree in Business, Computer Science, Engineering, or Design, or comparable work experience
- Preferred Qualifications: Experience building for AI systems, agents, or ML pipelines as primary consumers; experience building at companies where the data platform is the product, not a supporting system (e.g., Snowflake, Databricks, Elastic, MongoDB, Palantir)