Ontology Architect and Knowledge Modeling Specialist - SME
Chantilly, VA, United States2w ago
Key details
- Location
- Chantilly, VA, United States
- Work style
- Hybrid
- Level
- Senior
- Job type
- Full-time
- Experience
- 10–13 yrs
- Function
- Software engineering
- Focus area
- AI / ML
- Visa sponsorship
- Needs a Top Secret clearance
- Posted
- 2w ago
Skills
About the role
Education: Bachelor’s degree required
Experience: Minimum of 10 years of relevant experience
Position Summary
We are seeking a Knowledge Graph and Ontology Architect to design and implement enterprise knowledge graphs and semantic models that transform unstructured data into interconnected, machine-readable information.
This role develops domain-specific ontologies, taxonomies, and controlled vocabularies that capture complex relationships and business logic. Working closely with data scientists, software engineers, and AI architects, the architect integrates semantic frameworks with graph databases and AI pipelines to support entity resolution, semantic search, inference, and context-aware AI applications.
Responsibilities
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Lead the semantic architecture, design, and implementation of enterprise knowledge graphs and ontological models.
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Develop domain-specific ontologies, taxonomies, and controlled vocabularies using OWL, RDF, and SHACL.
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Translate complex business domains, relationships, and rules into structured semantic models.
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Design semantic schemas that support interoperability, inference, and metadata management across diverse repositories.
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Develop data harmonization pipelines that map and normalize structured and unstructured information into consistent semantic representations.
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Integrate semantic frameworks with enterprise graph databases, including GraphDB and Neo4j.
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Connect knowledge graphs with retrieval-augmented generation (RAG) pipelines and vector search systems.
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Establish governance practices, validation workflows, and data quality controls for semantic models and graph data.
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Define and maintain metadata standards, modeling conventions, and semantic architecture documentation.
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Collaborate with data scientists, software engineers, and AI architects to align semantic models with application and analytical requirements.
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Support entity resolution, semantic search, and context-aware AI through well-defined relationships and consistent data meaning.
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Identify and resolve inconsistencies across data sources to reduce information silos and improve interoperability.
Required Qualifications
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Must possess an active Top Secret Clearance
- Must be willing and able to obtain a polygraph
- Minimum of 10 years of relevant experience in semantic architecture, knowledge engineering, data architecture, ontology development, or related technical disciplines.
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Experience designing and implementing enterprise knowledge graphs and ontological models.
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Proficiency with semantic web standards, including Web Ontology Language (OWL), Resource Description Framework (RDF), and Shapes Constraint Language (SHACL).
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Experience developing domain-specific taxonomies, controlled vocabularies, and semantic schemas.
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Experience working with graph databases such as GraphDB and Neo4j.
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Understanding of semantic inference, entity resolution, metadata management, and cross-system interoperability.
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Experience integrating semantic models with RAG pipelines and vector search systems.
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Experience establishing data governance, validation, harmonization, and quality controls.
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Ability to translate complex business requirements into clear, maintainable semantic models.
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Strong analytical, technical documentation, communication, and collaboration skills.
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