Knowledge Graph Engineer – Entity Resolution & Graph Analytics
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
OntologyGraph Modeling
Design and evolve ontologies, schemas, and taxonomies for entities and relationships
Model complex, multi-source data into a coherent, queryable knowledge graph
Define and maintain graph data standards, naming conventions, and semantics
Entity ResolutionData Integration
Build entity resolution, deduplication, and record-linkage pipelines across disparate sources
Develop relationship and event extraction from structured and unstructured data using NLP / information-extraction techniques
Integrate curated data from the data engineering team into graph ingestion workflows
Implement confidence scoring, provenance, and source attribution for graph assertions
Graph AnalyticsQuery
Develop graph queries, traversals, and analytics (centrality, community detection, pathfinding, link analysis)
Expose graph capabilities via APIs and query interfaces for analysts and applications
Optimize graph storage, indexing, and query performance at scale
SecurityCompliance
Ensure the graph and its interfaces meet security requirements for sensitive environments
Implement access control, encryption, and secure handling of graph data
Support Authority to Operate (ATO) processes and compliance frameworks
Required Qualifications
Technical Expertise
4+ years of software or data engineering experience, including hands-on knowledge graph work
Experience 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 tooling
Understanding of ontology and semantic modeling (RDF, OWL, property graphs)
NLPData Integration
Experience with NLP / information extraction (spaCy, Hugging Face, or similar) for entity and relationship extraction
Experience integrating heterogeneous structured and unstructured data
Familiarity with vector embeddings and similarity-based linking
Domain Knowledge
Experience building or maintaining production knowledge graphs
Understanding of data provenance, confidence, and source attribution
Preferred Qualifications
Active security clearance or ability to obtain one
Experience in government, defense, or intelligence contracting environments
Familiarity with PAI/CAI data sources and entity-centric analysis
Experience with link analysis and network/graph analytics for investigative use cases
Knowledge of geospatial-temporal data in a graph context
Experience 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, SPARQL
Languages: Python (Java/Scala a plus)
NLP/ML: spaCy, Hugging Face, embeddings, entity-resolution frameworks
Data: Integration with platform data pipelines; RDF / property-graph models
Infrastructure: 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.