Senior Knowledge Graph Architect & AI Integration Lead

United Airlines; Chicago (IL); On-site; USD 112,000 - 147,000; Full time

Job summary

United Airlines is seeking an experienced Senior Knowledge Graph Developer to design, build, and scale enterprise knowledge graph initiatives. You will lead transforming siloed data into an interconnected semantic layer, bridging data engineering, ontology design, and AI/ML applications to power next-gen analytics.

The role emphasizes governance, performance, and collaboration with data science teams to integrate graph data with LLMs and RAG pipelines, using cloud-native, containerized workflows.

Qualifications

• 6–10+ years of software engineering or data architecture experience, with at least 4+ years in knowledge graph engineering.
• Hands-on experience with major graph platforms (Neo4j, Neptune, TigerGraph, Stardog).
• Proficient in Cypher, SPARQL, or Gremlin.
• Strong understanding of RDF, OWL, RDFS, SKOS and linked data principles.

Responsibilities

• Architecture & Design: Design scalable knowledge graph schemas for enterprise use.
• Ontology Engineering: Define ontologies, taxonomies, and semantic models across domains.
• Data Integration & Pipeline Development: Lead ETL/ELT pipelines to map data into the knowledge graph.
• Query & API Optimization: Develop complex graph queries and stable APIs for AI services.
• AI/ML Integration: Collaborate with data science teams to integrate graphs with LLMs, RAG, and embeddings.
• Governance & Performance: Ensure data quality, lineage, access control, and performance.
• Technical Leadership: Mentor engineers and drive graph technology adoption.

Skills

Knowledge graph

Graph databases

Python

Java

Cloud deployment

Docker/Kubernetes

API development

Tools

Neo4j

AWS Neptune

Stardog

TigerGraph

GraphDB

Job description

United Airlines is seeking an experienced Senior Knowledge Graph Developer to design, build, and scale enterprise knowledge graph initiatives. You will lead transforming siloed data into an interconnected semantic layer, bridging data engineering, ontology design, and AI/ML applications to power next-gen analytics.

The role emphasizes governance, performance, and collaboration with data science teams to integrate graph data with LLMs and RAG pipelines, using cloud-native, containerized workflows.