Principal GenAI Engineer

New York, NY, US • Posted 14 hours ago • Updated 7 hours ago

Full Time

No Travel Required

On-site

Depends on Experience

Fitment

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Job Details

Skills

Graph-RAG
Machine Learning

Summary

Role Overview

Turing is seeking a Principal GenAI Engineer with deep expertise in Large Language Models (LLMs) and Knowledge Graphs to lead enterprise-scale AI implementations for Fortune 500 clients.

This role focuses on building Graph-powered Retrieval-Augmented Generation (Graph-RAG) systems that combine structured semantic reasoning with advanced LLM architectures to deliver scalable, explainable, and production-grade AI solutions.

Key Responsibilities

Design and develop Graph-powered RAG (Graph-RAG) architectures integrating Knowledge Graphs with LLMs
Build and deploy enterprise-grade GenAI solutions using modern AI frameworks
Architect hybrid retrieval systems combining Knowledge Graphs and vector databases
Develop semantic data models, ontologies, and taxonomies for enterprise knowledge representation
Implement entity resolution, relationship extraction, and graph enrichment pipelines
Integrate structured graph reasoning with LLMs to improve explainability and reduce hallucinations
Deploy and scale GenAI solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform
Collaborate with data scientists, AI engineers, and business stakeholders to design scalable AI architectures
Lead technical strategy and implementation for enterprise AI knowledge systems

Required Qualifications

Experience

10+ years of experience building Machine Learning / AI systems
2+ years of hands-on experience with LLMs (RAG systems, AI agents, prompt engineering)
5+ years of production experience working with Knowledge Graphs

Technical Skills

Strong proficiency in Python
Experience with LangChain or LangGraph
Strong SQL and data modeling expertise
Experience deploying GenAI systems on cloud platforms (AWS / Azure / Google Cloud Platform)

Mandatory Knowledge Graph Expertise

Design and scale enterprise Knowledge Graph architectures
Develop ontologies, taxonomies, and semantic data models
Implement entity resolution and relationship extraction pipelines
Experience with graph databases such as:

Neo4j
Amazon Neptune

Strong hands-on experience with Cypher or similar graph query languages
Build hybrid retrieval systems combining Knowledge Graphs and vector databases
Integrate Knowledge Graph reasoning with LLMs to improve explainability and reduce hallucination

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91163612
Position Id: 8908223
Posted 14 hours ago

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