Generative AI Engineer (Knowledge Graph)

Job Title
Knowledge Graph & Generative AI Engineer

Overview / Summary

We are seeking a Knowledge Graph & Generative AI Engineer to work at the intersection of semantic data engineering, graph systems, and generative AI. This role focuses on transforming unstructured data into interconnected Knowledge Graphs (KGs) that support Retrieval-Augmented Generation (RAG), recommendation engines, and advanced reasoning models.

Key Responsibilities

• Design, build, and optimize scalable graph databases using technologies such as Neo4j and TigerGraph.
• Map ontologies and semantic web standards, including RDF and OWL.
• Develop embedding ingestion pipelines and integrate Knowledge Graphs with Large Language Models (LLMs).
• Enhance contextual retrieval, search capabilities, and generative AI responses through AI/LLM integration.
• Build and manage data processing approaches that parse and transform structured and unstructured data into graph-oriented formats.
• Architect entity resolution and relationship extraction workflows.
• Develop machine learning workflows to identify patterns and dependencies within complex datasets.

Required Qualifications

• Experience designing, building, and optimizing graph databases.
• Knowledge of graph technologies such as Neo4j or TigerGraph.
• Understanding of semantic web standards, including RDF and OWL.
• Experience developing embedding ingestion pipelines.
• Experience integrating Knowledge Graphs with Large Language Models (LLMs).
• Ability to process and transform structured and unstructured data into graph-oriented formats.
• Experience with entity resolution and relationship extraction.
• Experience developing machine learning workflows for complex data analysis.

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