Senior Knowledge Engineer (IC)

Location: Sterling, VA or Aurora, CO This is a hybrid position; however, it is required that successful candidate and report on-site on a regular basis and as-needed . Clearance: Active Top Secret clearance REQUIRED.

Position Overview

Crown Point Technologies is seeking a Senior Knowledge Graph & Semantic Solutions Engineer to support the development of an advanced software and data capability for a U.S. Intelligence Community customer. This position will focus on knowledge graphs, semantic data modeling, ontologies, graph technologies, and the integration of complex mission and engineering data.

The engineer will work closely with software engineers, AI/ML engineers, data engineers, ontologists, product vendors, and government stakeholders to develop semantic models and knowledge-driven applications. The work supports a mission-focused, space-based software capability and provides an opportunity to apply modern semantic technologies to complex engineering, mission, and operational data.

Candidates do not need experience with every technology listed below. We are particularly interested in engineers who understand knowledge representation, graph-based data architectures, or ontology-driven systems and can apply those concepts to real-world applications.

Responsibilities

Design, develop, extend, and maintain knowledge graph solutions supporting mission and engineering use cases. Develop semantic data models representing complex entities, relationships, systems, and mission concepts. Design and work with ontologies, RDF/OWL models, graph schemas, and semantic relationships. Develop and execute SPARQL queries and other graph-based data access mechanisms.

Use SHACL or similar technologies to validate semantic data and enforce data-quality constraints. Map source-system terminology and data structures into canonical semantic models. Develop crosswalks between enterprise, engineering, mission, and operational data sources. Evaluate existing ontology terms and models before introducing new concepts.

Develop ingestion and transformation processes to populate knowledge graphs from structured and unstructured data. Support entity resolution, relationship extraction, semantic enrichment, and data linking. Develop or integrate APIs and software services that interact with knowledge graph platforms. Support graph-enabled analytics, search, AI/ML, and application development.

Collaborate with AI/ML engineers to support Graph-RAG, semantic search, retrieval, and knowledge-grounded AI capabilities. Configure and extend commercial graph and semantic software platforms. Evaluate emerging graph, semantic, and knowledge representation technologies. Troubleshoot complex issues involving graph models, data integration, applications, and infrastructure.

Work directly with customer personnel, software vendors, engineers, architects, and other technical stakeholders. Desired Technical Skills Strong candidates will have experience in several of the following areas: Knowledge Graph & Semantic Technologies Knowledge graphs Graph databases RDF OWL SPARQL SHACL Ontology development Semantic data modeling Taxonomies and controlled vocabularies Entity resolution Relationship modeling Graph analytics Knowledge representation Experience with Siemens Graph Studio or similar enterprise knowledge graph platforms is highly desirable.

Software & Data Engineering Python, Java, JavaScript/TypeScript, or similar languages REST APIs Data transformation ETL/ELT JSON, XML, CSV, relational databases, and other common data formats Enterprise data integration Git and modern software development practices AI-Enabled Knowledge Systems Experience in any of the following areas is a plus: Retrieval-Augmented Generation Graph-RAG Semantic search Embeddings Vector search Natural language processing Information extraction AI agents LLM-enabled knowledge applications Deployment & Platform Technologies Docker Kubernetes Linux CI/CD Dev.

Sec. Ops Classified or disconnected computing environments Qualifications Active Top Secret U.S. Government security clearance required. Bachelor’s degree in Computer Science, Data Science, Information Systems, Software Engineering, Systems Engineering, Engineering, or a related technical discipline, or equivalent professional experience.

Professional experience with knowledge graphs, semantic technologies, ontologies, data engineering, information architecture, or a related field. Ability to understand complex technical domains and translate domain concepts into formal data models. Strong analytical and problem-solving skills. Ability to learn unfamiliar mission and engineering domains quickly.

Ability to collaborate across software, data, AI/ML, systems engineering, and customer teams. Strong written and verbal communication skills. Ability to explain semantic and data-modeling concepts to both technical and non-technical stakeholders. Salary $175,000 - $210,000 per year