Construction, General Contracting

Ontology Architect and Knowledge Modeling Specialist - SME

Chantilly, VAHybridFull TimeDistinguished / ArchitectPosted 15 days ago

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Required skills

Top Secret Clearance
polygraph
Ontology Architect
machine readable frameworks
trustworthy data models
enterprise knowledge graphs
ontological models
secure software development practices
process optimization
system health

Nice to have

Machine Learning
Computer Vision Models
object detection
classification
Cyber Security
Risk Management

Role summary

Fantom Corporation is seeking an Ontology Architect and Knowledge Modeling Specialist to design and implement enterprise knowledge graphs and ontological models for a mission-critical defense and intelligence program. The role involves transforming unstructured data into machine-readable intelligence, building trustworthy data models, and supporting specialist engineers. Qualifications include a Bachelor's degree with 10+ years of relevant experience or a Master's with less than 2 years, an active Top Secret Clearance, and expertise in machine-readable frameworks. The position also requires mentorship, process optimization, cross-team collaboration, and secure software development practices, with responsibilities for system monitoring.

Fantom Corporation is a mission-focused organization supporting critical programs across the defense and intelligence community. We partner with our customers to deliver high-impact technical solutions while fostering a culture built on trust, expertise, and long-term career growth. Must possess an active Top Secret Clearance Must be willing and able to obtain a polygraph

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

Lead the semantic architecture, design, and implementation of enterprise knowledge graphs and ontological models.

Develop domain-specific ontologies, taxonomies, and controlled vocabularies using OWL, RDF, and SHACL.

Translate complex business domains, relationships, and rules into structured semantic models.

Design semantic schemas that support interoperability, inference, and metadata management across diverse repositories.

Develop data harmonization pipelines that map and normalize structured and unstructured information into consistent semantic representations.

Integrate semantic frameworks with enterprise graph databases, including GraphDB and Neo4j.

Connect knowledge graphs with retrieval-augmented generation (RAG) pipelines and vector search systems.

Establish governance practices, validation workflows, and data quality controls for semantic models and graph data.

Define and maintain metadata standards, modeling conventions, and semantic architecture documentation.

Collaborate with data scientists, software engineers, and AI architects to align semantic models with application and analytical requirements.

Support entity resolution, semantic search, and context-aware AI through well-defined relationships and consistent data meaning.

Identify and resolve inconsistencies across data sources to reduce information silos and improve interoperability.

Required Qualifications

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.

Experience designing and implementing enterprise knowledge graphs and ontological models.

Proficiency with semantic web standards, including Web Ontology Language (OWL), Resource Description Framework (RDF), and Shapes Constraint Language (SHACL).

Experience developing domain-specific taxonomies, controlled vocabularies, and semantic schemas.

Experience working with graph databases such as GraphDB and Neo4j.

Understanding of semantic inference, entity resolution, metadata management, and cross-system interoperability.

Experience integrating semantic models with RAG pipelines and vector search systems.

Experience establishing data governance, validation, harmonization, and quality controls.

Ability to translate complex business requirements into clear, maintainable semantic models.

Strong analytical, technical documentation, communication, and collaboration skills.

#CJ Fantom Corp is a Software Development, Agile Cloud, Software Development, Cyber Security (Risk Management, Assessments & Authorization (A&A)), Data, AI Platform (Computer Vision Models), Podcasting Media Services, and IT Services provider. Established in 2015, Fantom Corp serves Federal customers with top-notch Cybersecurity Architects, Data Scientists/Analysts, Software Engineers/Developers, DevSecOps Engineers, Project Managers, Identity, Credential Access Management (ICAM) services , and Cloud-certified practitioners. We excel in delivering emerging technologies such as Artificial Intelligence (AI) and Machine Learning (ML) with a focus on identifying trends, object detection, and classification of structured and unstructured data. Fantom Corp possesses mastery in all aspects of digital audio production. We lead in the ideation and creation of efforts for clients who want to harness the power of podcasting. We guide them in selecting the right show format for their needs and goals. As a Small Business, we possess the innovation, speed and flexibility to meet your requirements. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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