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Job Title: Data Scientist – Knowledge Graphs & RAG / AI Consultant
Mode: Onsite
Type: Full-Time
Visas: / EAD
Location: Basking Ridge, NJ
Relocation: Accepted
Job Overview:
We are seeking a highly skilled Data Scientist / AI Consultant with strong expertise in Knowledge Graph technologies (RDF or Labeled Property Graphs) and hands-on experience building and integrating knowledge graph solutions into Retrieval-Augmented Generation (RAG) pipelines and Large Language Models (LLMs).
The ideal candidate will have proven experience implementing at least one production-grade Knowledge Graph solution, with strong proficiency in Neo4j, SPARQL, and Cypher, and the ability to design scalable graph-based AI architectures.
Key Responsibilities:
Job Title: Data Scientist – Knowledge Graphs & RAG / AI Consultant
Mode: Onsite
Type: Full-Time
Visas: / EAD
Location: Basking Ridge, NJ
Relocation: Accepted
Job Overview:
We are seeking a highly skilled Data Scientist / AI Consultant with strong expertise in Knowledge Graph technologies (RDF or Labeled Property Graphs) and hands-on experience building and integrating knowledge graph solutions into Retrieval-Augmented Generation (RAG) pipelines and Large Language Models (LLMs).
The ideal candidate will have proven experience implementing at least one production-grade Knowledge Graph solution, with strong proficiency in Neo4j, SPARQL, and Cypher, and the ability to design scalable graph-based AI architectures.
Key Responsibilities:
- Build, design, and manage Knowledge Graph solutions using RDF or LPG technologies
- Design and optimize graph data models in Neo4j for enterprise AI use cases
- Integrate Knowledge Graphs into RAG frameworks and LLM pipelines to improve contextual retrieval and reasoning
- Develop and execute complex queries using SPARQL and Cypher
- Translate business requirements into semantic models, ontologies, and graph structures
- Collaborate with AI/ML teams to implement graph-enhanced generative AI solutions
- Improve data connectivity and knowledge representation across enterprise systems
- Support architecture design and best practices for graph-based AI applications
- Strong hands-on experience with RDF, LPG, and Knowledge Graph technologies
- Proven expertise in Neo4j graph database
- Proficiency in graph query languages such as SPARQL and Cypher
- Experience integrating Knowledge Graphs with RAG pipelines and LLM-based AI systems
- At least one end-to-end implementation of a Knowledge Graph solution (mandatory)
- Strong understanding of semantic modeling, ontologies, and graph data structures
- Experience in AI/ML or Generative AI (preferred but not mandatory)