Why This Role Stands Out
This remote Senior Ontology Engineer role offers a competitive salary and the opportunity to build a foundational knowledge graph for a critical AI platform, directly impacting real users. You'll thrive here if you possess strong semantic technology skills, full-stack development experience, and an active US security clearance, eager to contribute to innovative AI solutions. Apply to join a fast-moving team delivering tangible results every sprint.
Quick Overview
Job Description
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.
- 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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