Knowledge Graph Engineer – Entity Resolution & Graph Analytics
United States掲載日 2026年9月13日
- 雇用形態
- Full Time
- 勤務形態
- Remote
- 給与
- 記載なし
この仕事について
Role Overview 3GIMBALS is seeking a Knowledge Graph Engineer to design, build, and maintain the knowledge graph that underpins our unclassified PAI/CAI-based analytic platform. This role is responsible for modeling ontologies, engineering entity resolution and relationship-extraction pipelines, and delivering graph-based analytics that connect people, organizations, locations, events, and other entities across large, heterogeneous data sources.
The ideal candidate blends data engineering, semantic modeling, and NLP to turn disparate data into a coherent, queryable graph that powers analytic discovery.
Key Responsibilities
- Ontology & Graph Modeling Design and evolve ontologies, schemas, and taxonomies for entities and relationshipsModel complex, multi-source data into a coherent, queryable knowledge graphDefine and maintain graph data standards, naming conventions, and semantics Entity Resolution & Data Integration Build entity resolution, deduplication, and record-linkage pipelines across disparate sourcesDevelop relationship and event extraction from structured and unstructured data using NLP / information-extraction techniquesIntegrate curated data from the data engineering team into graph ingestion workflowsImplement confidence scoring, provenance, and source attribution for graph assertions Graph Analytics & Query Develop graph queries, traversals, and analytics (centrality, community detection, pathfinding, link analysis)Expose graph capabilities via APIs and query interfaces for analysts and applicationsOptimize graph storage, indexing, and query performance at scale Security & Compliance Ensure the graph and its interfaces meet security requirements for sensitive environmentsImplement access control, encryption, and secure handling of graph dataSupport Authority to Operate (ATO) processes and compliance frameworks
Required Qualifications
- Technical Expertise4+ years of software or data engineering experience, including hands-on knowledge graph workExperience with graph databases (Neo4j, Amazon Neptune, TigerGraph, JanusGraph, or similar)Proficiency with graph query languages (Cypher, Gremlin, or SPARQL)Strong programming skills in Python (Java or Scala a plus)Experience with entity resolution / record-linkage techniques and toolingUnderstanding of ontology and semantic modeling (RDF, OWL, property graphs) NLP & Data Integration Experience with NLP / information extraction (spaCy, Hugging Face, or similar) for entity and relationship extractionExperience integrating heterogeneous structured and unstructured dataFamiliarity with vector embeddings and similarity-based linking Domain Knowledge Experience building or maintaining production knowledge graphsUnderstanding of data provenance, confidence, and source attribution
Preferred Qualifications
- Active security clearance or ability to obtain oneExperience in government, defense, or intelligence contracting environmentsFamiliarity with PAI/CAI data sources and entity-centric analysisExperience with link analysis and network/graph analytics for investigative use casesKnowledge of geospatial-temporal data in a graph contextExperience integrating knowledge graphs with LLM / RAG systems (GraphRAG)Familiarity with federal compliance frameworks (FedRAMP, FISMA, NIST 800-53) Technical Environment Graph: Neo4j / Neptune / JanusGraph;
- Cypher, Gremlin, SPARQLLanguages: Python (Java/Scala a plus)NLP/ML: spaCy, Hugging Face, embeddings, entity-resolution frameworksData: Integration with platform data pipelines;
- RDF / property-graph modelsInfrastructure: Docker, Kubernetes, cloud platforms (AWS GovCloud, Azure Government)Security: RBAC, encryption, secure APIs This role owns the connective tissue of the platform: the ontology and graph that let analysts move from isolated records to the relationships, networks, and patterns that drive insight.
- Salary: $130000 - $180000 per year