Knowledge Graph Engineer

Role - Knowledge Graph Engineer

Client - UHG

Key Responsibilities

• Design and implement enterprise knowledge graph architectures aligned with business and data architecture principles.
• Develop graph-based representations of business entities, concepts, relationships, events, and dependencies.
• Translate enterprise ontologies and semantic models into production-ready knowledge graph implementations.
• Design and implement entity relationship models across Finance, Accounting, and other enterprise domains.
• Build and maintain knowledge graphs using graph databases and semantic graph technologies.
• Develop graph data models, schemas, relationships, constraints, and query patterns.
• Implement data ingestion and transformation pipelines to populate knowledge graphs from enterprise source systems and data products.
• Integrate structured, semi-structured, and unstructured data into knowledge graph solutions where appropriate.
• Develop entity resolution and relationship-mapping approaches to establish connections across disparate data sources.
• Implement graph queries and traversal patterns to support business and analytical use cases.
• Develop context-aware search and semantic discovery capabilities using knowledge graph relationships and metadata.
• Support graph-based reasoning and inference to derive meaningful relationships and business context.
• Integrate knowledge graphs with AI/ML and Large Language Model (LLM) applications.
• Support Retrieval-Augmented Generation (RAG) architectures using knowledge graphs and hybrid retrieval approaches.
• Develop graph-based context retrieval mechanisms to improve LLM accuracy, relevance, and explainability.
• Integrate knowledge graphs with vector search, embeddings, semantic search, and AI agent architectures.
• Design APIs and services that expose graph-based knowledge to downstream applications.
• Implement graph validation, quality checks, lineage, and monitoring to ensure knowledge graph reliability.
• Optimize graph queries, data models, and storage structures for scalability and performance.
• Collaborate with Ontology Architects to ensure graph implementations accurately reflect approved ontology models.
• Work with Data and Semantic Architects to maintain alignment between physical data, semantic models, and knowledge graphs.
• Develop technical documentation covering graph architecture, data models, ingestion pipelines, queries, and APIs.
• Contribute to standards and best practices for enterprise knowledge graph development and governance.
• Strong hands-on experience developing knowledge graph solutions .
• Experience with graph databases and graph technologies.
• Strong understanding of entity-relationship modeling and graph data modeling .
• Experience designing scalable knowledge graph architectures.
• Strong knowledge of graph querying and traversal concepts.
• Experience with technologies such as Neo4j, RDF, OWL, SPARQL, property graphs , or comparable technologies.
• Experience building data ingestion and transformation pipelines for graph databases.
• Understanding of ontology and semantic modeling concepts.
• Experience integrating knowledge graphs with AI/ML and LLM applications .
• Understanding of RAG, semantic search, embeddings, vector databases, and contextual retrieval.
• Experience developing APIs or services that expose knowledge graph capabilities.
• Strong understanding of data quality, metadata, lineage, and governance.
• Strong programming skills in languages such as Python, Java, Scala, or comparable languages.
• Strong analytical and problem-solving capabilities.