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.CLEARANCE REQUIREMENTS:: Department of Defense Secret security clearance is required at time of hire. Applicants selected will be subject to a U.S. Government security investigation and must meet eligibility requirements for access to classified information. Due to the nature of work performed within our facilities, U.S. citizenship is required.Responsibilities for this PositionWhat You'll OwnEnterprise 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 OwnPod-specific data modeling — that's the Data/Ontology Engineer's role within each podAI application development or engineeringEnterprise system administration or data engineering pipelinesWhat Makes This Role DifferentYou 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 QualificationsBachelor’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 experienceExperience designing enterprise-level data architectures, knowledge models, or information taxonomies that span multiple business domainsStrong understanding of ontology and semantic modeling concepts — you can work fluently with knowledge graph engineers and data modelersSystems engineering mindset — you think about interfaces, dependencies, integration points, and emergent behavior across interconnected systemsExperience working across organizational boundaries — you have built consensus on shared standards across teams that had their own ways of doing thingsStrong communication skills — you can explain data relationships to business stakeholders and architectural constraints to engineersU.S. citizenship required. Department of Defense Secret security clearance is required at time of hire.Preferred QualificationsExperience with knowledge graphs, semantic web technologies, or enterprise taxonomy managementExperience with enterprise data platforms (Palantir Foundry, Snowflake, or similar) and their ontology or semantic layer capabilitiesBackground in manufacturing, defense, or complex enterprise environments with multiple interacting business systemsExperience defining metadata standards, business glossaries, or data governance frameworks at an enterprise levelFamiliarity with how AI/LLM systems consume structured knowledge — RAG architectures, knowledge-grounded reasoning, semantic searchWhat Sets You ApartYou 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.DetailsRemote — 100% telework9/80 scheduleDefense industry experience is not requiredSalary NoteThis estimate represents the typical salary range fo