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Niche senior GenAI specialization reduces candidate pool despite Bengaluru metro location.
Highly specialized GenAI and knowledge-graph skills make cross-industry transfers difficult.
Explicit 10–14 years plus mandatory GenAI, LLM, RAG, LangChain and cloud experience enforces strict filters.
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Lead design and deployment of scalable, production-grade Gen AI solutions on cloud platforms (AWS, Azure, or GCP) for enterprise clients.
Own hands-on development and integration of Large Language Models with Retrieval-Augmented Generation (RAG), AI Agents, and prompt engineering techniques.
Drive innovation by leveraging Knowledge Graphs and advanced graph databases to enhance AI explainability and reduce hallucination in LLM outputs.
10+ years of experience in Machine Learning/Artificial Intelligence.
Minimum 2 years of hands-on experience with Large Language Models (LLMs).
Strong proficiency in Python, LangChain, Lang Graph, SQL, and deployment on AWS, Azure, or GCP.
Experience designing and delivering scalable, production-grade AI solutions for enterprise clients.
Demonstrated expertise in integrating LLMs with RAG and AI Agents in production environments.
Experience with Knowledge Graph architecture, semantic data modeling, and graph databases like Neo4j or Amazon Neptune.
Skilled in developing hybrid retrieval systems combining Knowledge Graphs and vector databases to improve model reliability and explainability.