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

- What Were Looking For

8-13 years of experience in ML/AI systems

2+ years hands-on experience with LLMs (RAG, agents, prompt engineering)

Strong proficiency in Python, LangChain, LangGraph, and SQL

Experience deploying GenAI systems on AWS / Azure / GCP

Positive to Have - Knowledge Graph Expertise

Design and scale enterprise Knowledge Graph architectures

Develop ontologies, taxonomies, and semantic data models

Implement entity resolution, relationship extraction, and graph enrichment

Experience with Neo4j, Amazon Neptune, or similar graph databases

Strong hands-on experience with Cypher (or similar graph query languages)

Build hybrid retrieval systems combining Knowledge Graphs + vector databases

Integrate structured graph reasoning with LLMs to reduce hallucination and improve explainability

📌 Principal GenAI Engineer (Bengaluru)
🏢 Tanisha Systems
📍 Bengaluru