Knowledge Graph/Ontology Engineer

Peraton•Basking Ridge, NJ

4d•$104,000 - $166,000

About The Position

Peraton Labs is seeking a knowledge graph engineer to extend and maintain the knowledge graph that underpins a generative AI-powered analytical platform. This role models entities and their relationships, enabling cross-portfolio queries, entity linking, and relationship-based analytics that connect elements into a navigable knowledge structure.

Requirements

Minimum of 8+ years of experience with a Bachelor's degree, 6+ years with a Master's degree, or 3+ years with a PhD in Computer Science, Information Science, or related field
3+ years of experience with knowledge representation, ontology engineering, or graph databases
Proficiency with RDF, OWL, SPARQL, and semantic web technologies
Experience with graph databases (Oxigraph, Blazegraph, Neo4j, or similar)
Strong Python proficiency; experience with RDF libraries (rdflib, or similar)
Understanding of ontology design patterns and best practices
Experience with entity resolution and knowledge base population
Familiarity with linked data principles and standards
US Citizenship with the ability to obtain/maintain a Secret clearance

Nice To Haves

Experience with defense or government ontologies (DoD Architecture Framework, NIEM)
Experience with knowledge graph embedding and graph neural networks
Knowledge of provenance tracking and data lineage in knowledge graphs

Responsibilities

Design and implement ontologies for various entities
Extend the knowledge graph with entity types and relationship models
Build entity extraction and linking pipelines that populate the knowledge graph from both structured and unstructured sources
Enable cross-portfolio queries
Develop SPARQL query templates and APIs for common analytical patterns
Implement knowledge graph quality assurance: consistency checks, completeness monitoring, and conflict resolution
Design the knowledge graph update pipeline for incremental data ingestion
Collaborate with NLP Engineers on entity resolution and with Data Fusion Engineers on relationship validation