Principal GenAI Engineer - Knowledge Graph & Graph RAG

First Soft Solutions LLC; Chennai District; Hybrid; INR 3,500,000 - 6,500,000; Full time

Job summary

First Soft Solutions LLC in Bengaluru is seeking a Principal GenAI Engineer to lead the design, development, and deployment of enterprise-grade Generative AI solutions for Fortune 500 clients. This role requires deep expertise in LLMs, RAG, Knowledge Graphs, and Graph-RAG architectures to deliver scalable, production-ready AI applications.

The candidate will mentor engineering teams, collaborate with data scientists and software engineers, and drive best practices for GenAI development and

Qualifications

• 8-14 years of experience in Software Engineering, ML, or AI.
• 2+ years hands-on experience with LLMs.
• Strong expertise in Python, LangChain, LangGraph, SQL.

Responsibilities

• Design and implement enterprise-scale GenAI solutions using LLMs.
• Architect Graph-RAG systems combining Knowledge Graphs with vector search.
• Build intelligent AI agents using LangChain, LangGraph, and orchestration frameworks.
• Develop and optimize RAG pipelines for enterprise knowledge discovery.
• Design scalable Knowledge Graph architectures, ontologies, and taxonomies.
• Implement entity resolution, relationship extraction, graph enrichment, and semantic reasoning.
• Integrate Knowledge Graphs with vector databases to reduce hallucinations.
• Deploy and manage AI workloads on AWS, Azure, or GCP.
• Collaborate with data scientists and engineers to deliver production-grade AI solutions.
• Mentor teams and establish best practices for GenAI development.

Skills

Python

LangChain

LangGraph

SQL

LLMs

RAG

AI Agents

Prompt Engineering

Vector Databases

Cloud Deployment

Education

Bachelor's or Master's in CS/AI/ML

Tools

AWS

Azure

GCP

Neo4j

Amazon Neptune

TigerGraph

Nebula Graph

Cypher

Docker

Job description

Principal GenAI Engineer Knowledge Graph & Graph RAG

Location

Bengaluru (Hybrid 3 Days Work from Office)

Employment Type

Full-Time

Experience

8 14 Years

Job Summary

We are seeking an experienced Principal GenAI Engineer to lead the design, development, and deployment of enterprise-grade Generative AI solutions for Fortune 500 clients. The ideal candidate will have deep expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Knowledge Graphs, and Graph-RAG architectures, enabling the delivery of scalable, explainable, and production-ready AI applications. This role requires strong technical leadership, hands‑on development, and collaboration with cross-functional teams to build next‑generation AI solutions.

Key Responsibilities

• Design and implement enterprise-scale Generative AI solutions using Large Language Models (LLMs).
• Architect and develop Graph-RAG systems by combining Knowledge Graphs with vector search for accurate, context‑aware AI responses.
• Build intelligent AI agents using LangChain, LangGraph, and modern orchestration frameworks.
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge discovery.
• Design, implement, and maintain scalable Knowledge Graph architectures, semantic models, ontologies, and taxonomies.
• Implement entity resolution, relationship extraction, graph enrichment, and semantic reasoning.
• Integrate Knowledge Graphs with vector databases to improve AI explainability and reduce hallucinations.
• Deploy and manage AI workloads on AWS, Azure, or Google Cloud Platform (GCP).
• Collaborate with data scientists, software engineers, and business stakeholders to deliver production‑ready AI solutions.
• Mentor engineering teams and establish best practices for GenAI development and deployment.

Required Skills

• 8 14 years of experience in Software Engineering, Machine Learning, or Artificial Intelligence.
• 2+ years of hands‑on experience developing applications using Large Language Models (LLMs).
• Strong expertise in:
  • Python
  • LangChain
  • LangGraph
  • SQL
• Experience with:
  • Retrieval-Augmented Generation (RAG)
  • AI Agents
  • Prompt Engineering
  • Vector Databases
• Experience deploying AI applications on AWS, Azure, or GCP.
• Strong understanding of enterprise AI architecture, scalability, and performance optimization.

Preferred Qualifications Knowledge Graph Expertise

• Experience designing and scaling enterprise Knowledge Graph solutions.
• Strong understanding of:
  • Ontologies
  • Taxonomies
  • Semantic Data Models
  • Entity Resolution
  • Relationship Extraction
  • Graph Enrichment
• Hands‑on experience with graph databases such as:
  • Neo4j
  • Amazon Neptune
  • TigerGraph
  • Nebula Graph
• Proficiency with graph query languages such as Cypher or equivalent.
• Experience building hybrid retrieval architectures combining Knowledge Graphs and Vector Databases.
• Ability to integrate structured graph reasoning with LLMs to improve explainability and minimize hallucinations.

Nice to Have

• Experience with Azure AI Foundry, Amazon Bedrock, Google Vertex AI, or OpenAI APIs.
• Familiarity with embedding models, reranking techniques, and semantic search.
• Experience with MLOps, Docker, Kubernetes, and CI/CD pipelines.
• Knowledge of Graph Data Science (GDS), Graph Analytics, and Explainable AI (XAI).

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.