Salary
≈ $93k – $195k per year (Estimated)
Location
Remote (United States)
Seniority
Senior
Employment
Full-Time
Overview
Company
Impact
Profile match
InterImage is an IT services and consulting firm headquartered in Arlington, Virginia. Founded in 1996, the company delivers software engineering, modern IT infrastructure, and digital transformation services primarily to U.S. federal government agencies, military organizations, and law enforcement.
PixelRain AI is a small, fast-moving AI company delivering an AI-powered product-lifecycle knowledge platform for a U.S. Department of War (DoW) customer: governed ingestion of technical documents, an enterprise ontology and knowledge graph, and generative-AI applications that draft maintenance-planning products and answer engineering questions with citations - running in the customer's cloud environment, with an offline variant for disconnected use. Small team, real users, working software demonstrated every sprint.
Salary: 175,000 - 228,000
Active US Security Clearance Required
What you'll do
- 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: RDF triple store (Apache Jena/Fuseki or similar), SHACL validation, 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.
- Carry normal full-stack development work alongside the ontology work - Python services, web UI, AWS.
- Work in a small Scrum team; 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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