Senior Ontology Engineer

🔥 8 minutes ago

⚔️ Virginia – Remote

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💵 $175k - $228k / year

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 0%

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Logo of InterImage

InterImage

51 - 200 employees

Founded 1996

🏛️ Government

🤖 Artificial Intelligence

🔒 Cybersecurity

Government • Artificial Intelligence • Cybersecurity

InterImage is a US-based IT modernization and systems-integration firm that delivers intelligent automation and mission-focused technology services to government and commercial clients. The company specializes in GenAI/AI & ML, Robotic Process Automation (RPA), agile software development, data analytics, systems engineering and integration, cybersecurity, and cloud services. InterImage holds government contract vehicles (GSA MAS, SeaPort-NxG, ITES-3S) and targets defense, law enforcement, transportation, civilian, and commercial customers to modernize IT, automate routine processes, and improve operational productivity.

📋 Description

• Design, build, and maintain the enterprise ontology (BFO/CCO-aligned) and controlled vocabularies, and map source-system data into them • Build and manage the knowledge graph using an RDF triple store, SHACL validation, and SPARQL queries • Build the governed ingestion path so extracted content lands in the graph with provenance and confidence, and connect the graph to retrieval and GenAI applications • Perform full-stack development alongside ontology work, including Python services, web UI, and AWS • Work in a small Scrum team and demo working software every sprint

🎯 Requirements

• Active Secret OR Top Secret Clearance Required • 5+ years of hands-on semantic-technology work: OWL, RDF/Turtle, SHACL, and SPARQL • Experience building ontologies aligned to an upper ontology — BFO and CCO strongly preferred • Production experience with a triple store (Apache Jena/Fuseki, RDF4J, or similar) • Solid general software engineering: Python, APIs, Git — able to handle full-stack tasks (web + AWS), not ontology-only • Working familiarity with LLMs and RAG — you’ve connected structured knowledge to generative applications

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