Knowledge Graph Engineer

Location: Northern VA, Washington, DC, Bethesda, MD, Colorado Springs, CO

Clearance: Active Top Secret clearance REQUIRED. 

Position Overview

Crown Point Technologies is seeking aSemantic Knowledge Graph Engineer to support the development and implementation of graph-based capabilities for a U.S. Government mission customer.

The engineer will help advanceObject-Based Intelligence (OBI) by transitioning information from traditional document-centric representations into anentity-focused, semantically connected knowledge graph. Using RDF, SPARQL, ontologies, and related semantic technologies, the engineer will integrate information from disparate operational, intelligence, and analytical sources to create a unified representation of objects, entities, relationships, activities, and operational context.

This role combinesknowledge graph engineering, semantic data modeling, data integration, and software engineering. The ideal candidate has experience working with RDF-based graph technologies and is comfortable translating complex mission concepts and source-system data into reusable semantic models.

Key Responsibilities

• Design, develop, and maintainRDF-based knowledge graphs supporting intelligence, operational, and analytical missions.
• Develop semantic representations of objects, entities, events, activities, relationships, and associated operational context.
• Develop and maintainontologies, RDF schemas, controlled vocabularies, and semantic data models.
• Write and optimizeSPARQL queries to retrieve, analyze, transform, and validate graph data.
• Map structured, semi-structured, and unstructured source data into canonical RDF-based semantic models.
• Develop mappings and crosswalks between source-system concepts and enterprise or mission ontologies.
• Evaluate existing ontology classes and properties before introducing new semantic concepts.
• Develop and maintainSHACL shapes and validation rules to support data quality and conformance requirements.
• Integrate disparate operational, intelligence, and analytical data to create connected, entity-centric views of mission information.
• Support entity identification, reconciliation, linking, and relationship modeling across multiple data sources.
• Develop data ingestion and transformation processes that convert source data intoRDF triples and knowledge graph representations.
• Support graph-based analytics that identify relationships, patterns, dependencies, and operational connections across complex datasets.
• Work with analysts, mission users, software engineers, data engineers, and systems engineers to translate operational requirements into semantic models and technical solutions.
• Support integration of semantic knowledge graphs with applications, APIs, analytical tools, and enterprise data platforms.
• Document ontologies, data mappings, semantic models, interfaces, engineering decisions, and technical architectures.
• Support testing, troubleshooting, deployment, and continuous improvement of graph-based capabilities within mission environments.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Information Systems, Engineering, Mathematics, or a related discipline; equivalent professional experience may be considered.
• Experience developing or working withRDF-based knowledge graphs or semantic data systems.
• Hands-on experience withRDF and SPARQL.
• Experience developing, extending, or working withontologies and semantic data models.
• Experience integrating and transforming data from multiple heterogeneous sources.
• Experience with programming or scripting languages such asPython, Java, or JavaScript.
• Understanding of data modeling, entity relationships, and data integration concepts.
• Ability to translate complex real-world concepts and relationships into formal semantic representations.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to collaborate with both technical teams and mission-focused stakeholders.

Desired Qualifications

Experience with one or more of the following is highly desirable:

• RDF, RDFS, OWL, and SPARQL
• SHACL and semantic data validation
• Ontology development and ontology engineering
• Knowledge graph design and implementation
• Semantic reasoning and inference
• Upper-level or common ontologies
• Taxonomies, controlled vocabularies, and terminology management
• Entity resolution, identity reconciliation, or semantic data integration
• Mapping relational, JSON, XML, or other source data into RDF
• SPARQL query optimization and graph analytics
• Triple stores or RDF graph platforms such asAnzo, Stardog, GraphDB, Apache Jena, Amazon Neptune RDF, or similar technologies
• Object-Based Intelligence (OBI) concepts and workflows
• Intelligence Community or Department of War mission environments
• All-source intelligence or operational data integration
• REST APIs and enterprise application integration
• Python-based data transformation and automation
• Containerized environments using Docker, Kubernetes, or OpenShift
• DevSecOps and CI/CD environments
• Applying AI/ML or natural language processing techniques to semantic or knowledge graph data
• Data provenance, metadata management, and semantic interoperability
• Working within classified environments