Ontology Systems Engineer
Listed on 2026-07-01
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IT/Tech
Data Engineering, Information & Knowledge Management
Ontology Systems Engineer
Ontology Systems Engineer : US-Telework-Telework Required Clearance:
Secret Category:
Engineering-Systems
Employment Type:
Full Time Hiring Company:
General Dynamics Mission Systems, Inc. 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.
- 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.
- 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
- 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.
- Bachelors degree in Systems Engineering, Computer Science, Information Science, or a related field, plus 8 years of experience; or Masters 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
- U.S. citizenship required. Department of Defense Secret security clearance is required at time of hire.
- 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,…
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