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# Knowledge Graph Architect

- **Company:** Eliassen Group
- **Location:** Charleston, WV, United States (Remote available)
- **Salary:** $208,000 - $249,600
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Architecture, Information Engineering, Graph Database, Operational Data Store, Semantic Web, Enterprise Data Management, Retrieval-Augmented Generation, Large Language Models, Agentic-AI, Knowledge Engineering, Virtual Agents, Entity Resolution, Graph RAG, Semantic Modeling
- **Published:** November 1, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3485649223&tx=JL6963FFI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance., * Strong experience in knowledge graph architecture, ontology development, semantic architecture, knowledge engineering, enterprise/data architecture, or AI/ML architecture.

 * Hands-on experience working with knowledge graphs, ontologies, semantic modeling, or graph databases.
 * Understanding of RAG/GraphRAG, LLMs, AI agents, and enterprise data integration.
 * Experience defining relationships and mappings across complex, disparate enterprise data sources.
 * Ability to translate complex business and operational concepts into scalable technical architectures.
 * Strong communication skills and ability to work across both technical teams and business/domain SMEs.

## Description

Our client is seeking a Knowledge Graph Architect to lead the architecture and technical strategy for a construction-focused ontology, knowledge graph, and AI knowledge platform. You will connect historical project and operational data across estimating, scheduling, project controls, field execution, equipment, cost, and lessons learned to create a reusable knowledge foundation that can support AI, GraphRAG, LLM, and agent-based applications. This role requires expertise in designing and building enterprise knowledge graphs and ontologies applied to modern AI use cases., * Architect and develop an enterprise ontology and knowledge graph for complex construction and project data.

 * Define relationships across projects, activities, estimates, schedules, cost codes, crews, equipment, quantities, production rates, risks, changes, and outcomes.
 * Evaluate and incorporate relevant standards, including IFC, buildingSMART, LandInfra, and semantic web standards.
 * Integrate enterprise data from multiple operational and project systems into the knowledge architecture.
 * Design and guide GraphRAG, LazyGraphRAG, RAG, and AI agent architectures.
 * Establish standards for ontology governance, provenance, entity resolution, cross-system mappings, and knowledge quality.
 * Partner with domain SMEs, enterprise architecture, data engineering, AI engineering, and technology teams.
 * Design experiments to evaluate whether structured enterprise knowledge improves AI answer quality compared with traditional RAG and LLM approaches.