Ontology Systems Engineer

Basic Qualifications

Bachelor's degree in Systems Engineering, or a related Science, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus a minimum of 6 years of relevant experience.

Responsibilities for this Position

What You'll Own

• Enterprise knowledge architecture. Define and maintain the overarching structure that connects domain-specific ontologies across pods. Manage the relationships between business vocabularies, taxonomies, and data models at the enterprise level.
• Cross-domain consistency. Ensure that business concepts defined in one pod are compatible with concepts in other pods. Resolve naming conflicts, semantic overlaps, and definitional inconsistencies before they become integration problems.
• Metadata and tagging standards. Establish enterprise-wide standards for metadata, tagging, classification, and search structures. Build the knowledge infrastructure that makes enterprise data findable, reusable, and machine-readable.
• Business glossary governance. Own the enterprise business glossary — the authoritative source for what terms mean across the organization. Work with data owners and business stewards to maintain accuracy.
• Knowledge repository architecture. Design the structures that store and expose enterprise knowledge — knowledge graphs, semantic catalogs, taxonomy services. Ensure AI agents can discover and traverse enterprise knowledge programmatically.

What You Won't Own

• Pod-specific data modeling — that's the Data/Ontology Engineer's role within each pod
• AI application development or engineering
• Enterprise system administration or data engineering pipelines

What Makes This Role Different

• You are building the connective tissue between multiple AI modernization efforts. Without your work, each pod builds an island. With it, they build a continent.
• Your knowledge architecture directly enables cross-domain AI reasoning. An agent that can connect HR data to manufacturing data to supply chain data — that capability starts with your architecture.
• This role requires both systems thinking and business fluency. You need to understand how manufacturing processes, HR workflows, and CRM systems relate at a business level, not just a data level.

Required Qualifications

• Bachelor’s degree in Systems Engineering, Computer Science, Information Science, or a related field, plus 8 years of experience; or Master’s degree plus 6 years of experience
• Experience designing enterprise-level data architectures, knowledge models, or information taxonomies that span multiple business domains
• Strong understanding of ontology and semantic modeling concepts — you can work fluently with knowledge graph engineers and data modelers
• Systems engineering mindset — you think about interfaces, dependencies, integration points, and emergent behavior across interconnected systems
• Experience working across organizational boundaries — you have built consensus on shared standards across teams that had their own ways of doing things
• Strong communication skills — you can explain data relationships to business stakeholders and architectural constraints to engineers
• S. citizenship required. Department of Defense Secret security clearance is required at time of hire.

Preferred Qualifications

• Experience with knowledge graphs, semantic web technologies, or enterprise taxonomy management
• Experience with enterprise data platforms (Palantir Foundry, Snowflake, or similar) and their ontology or semantic layer capabilities
• Background in manufacturing, defense, or complex enterprise environments with multiple interacting business systems
• Experience defining metadata standards, business glossaries, or data governance frameworks at an enterprise level
• Familiarity with how AI/LLM systems consume structured knowledge — RAG architectures, knowledge-grounded reasoning, semantic search

What Sets You Apart

• You see the enterprise as a system of systems. You instinctively look for the connections between domains, not just the domains themselves.
• You have resolved vocabulary conflicts across organizations and made the shared definition stick.
• You can hold the big picture and the details at the same time — enterprise architecture in the morning, specific field mappings in the afternoon.
• You build for reuse. Your architectures are designed to accommodate domains that don't exist yet, not just the ones in front of you today.
• You are known as the person who can explain how everything connects. People come to you when they need to understand the whole.

Details

• Remote — 100% telework
• 9/80 schedule