Remote Knowledge Graph Architect for AI‑Driven Construction

Eliassen Group; Cheyenne (WY); Remote; USD 138,000 - 165,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401k with company matching

Life insurance

Sick time as required by law

Job summary

Eliassen Group is seeking a Knowledge Graph Architect to lead the architecture and strategy for a construction-focused ontology, knowledge graph, and AI knowledge platform.

You will connect historical project 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.

Qualifications

• Strong experience in knowledge graph architecture and ontology development.
• Hands-on work with knowledge graphs, semantic modeling, or graph databases.
• Understanding of RAG/GraphRAG, LLMs, AI agents, and enterprise data integration.
• Ability to translate complex business concepts into scalable technical architectures.

Responsibilities

• Architect and develop an enterprise ontology and knowledge graph for construction and project data.
• Define relationships across projects, estimates, schedules, costs, and outcomes.
• Evaluate standards like IFC, buildingSMART, LandInfra, and semantic web specs.
• Integrate enterprise data from multiple systems into the knowledge architecture.
• Design GraphRAG, LazyGraphRAG, RAG, and AI agent architectures.
• Establish ontology governance, provenance, entity resolution, and cross-system mappings.
• Collaborate with SMEs, enterprise architecture, data and AI engineering teams.
• Design experiments to test AI answer quality with structured knowledge.

Skills

Knowledge graph

Ontology development

Semantic modeling

Graph databases

AI/ML architecture

Job description

Eliassen Group is seeking a Knowledge Graph Architect to lead the architecture and strategy for a construction-focused ontology, knowledge graph, and AI knowledge platform.

You will connect historical project 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.