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Job details:
Min 10+ years of exp mandatory
Role Overview
The Principal AI Engineer will lead the design and deployment of enterprise-scale GenAI solutions for Fortune 500 clients. The role involves developing production-grade Graph-RAG systems, optimizing LLM-based applications, owning Python/SQL codebases, integrating solutions with cloud platforms, and providing technical leadership to AI/ML engineering teams.
Key Responsibilities include:
Lead the design and deployment of LLM-based solutions using RAG, prompt engineering, and agent architectures
Build scalable and reusable Python/SQL components
Design and optimize GenAI applications on AWS/Azure/GCP
Work closely with Data Scientists, Product Owners, and Business SMEs
Provide technical leadership and mentor engineering teams
Develop scalable Graph-RAG and Knowledge Graph-based AI solutions
MUST HAVE:
LLM-based enterprise AI solutions
Retrieval-Augmented Generation (RAG)
Agent-based architectures
Graph-powered RAG / Graph-RAG
Python and SQL
LangGraph / LangChain
Cloud deployment – AWS / Azure / GCP
Knowledge Graphs and semantic reasoning
Good to Have:
Neo4j / Amazon Neptune / similar graph databases
Cypher or similar graph query languages
Ontologies, taxonomies, and semantic data models
Entity resolution, relationship extraction, and graph enrichment
Hybrid retrieval using Knowledge Graphs + Vector Databases
Experience integrating structured graph reasoning with LLMs
Click on Apply to know more.