Generative AI Developer LangChain LangGraph and RAG Expert

Kairotic Cybernatics services; Dadri; On-site; INR 6,75,000 - 9,00,000; Full time

Job summary

A forward-thinking company is seeking a talented Generative AI Developer to innovate with LangChain, LangGraph, and RAG technologies. In this exciting role, you will design and deploy advanced AI solutions, focusing on building modular applications and optimizing knowledge graphs for real-time data inference. You'll have the opportunity to work with cutting-edge models and cloud platforms, ensuring scalability and performance while addressing fairness and security. If you are passionate about AI and eager to contribute to transformative projects, this position offers a dynamic environment to grow and excel.

Qualifications

• Proficient in LangChain, LangGraph, RAG, and vector databases.
• Strong Python skills with hands-on experience in LLMs.

Responsibilities

• Build AI-powered applications with LangChain and optimize knowledge graphs.
• Create multi-agent systems and enhance generative AI with retrieval systems.

Skills

LangChain

LangGraph

Python

Multi Agent Framework

Retrieval-Augmented Generation (RAG)

LLMs (GPT, BERT, LLAMA)

Cloud Integration

Tools

Hugging Face

TensorFlow

AWS

Azure

GCP

Pinecone

Weaviate

Neo4j

Job description

Generative AI Developer LangChain LangGraph and RAG Expert

Job Title: Generative AI Developer – LangChain, LangGraph, and RAG Expert

Overview:

Seeking a skilled Generative AI Developer with expertise in LangChain, LangGraph, Multi Agent Framework, and Retrieval-Augmented Generation (RAG). You’ll design and deploy cutting-edge AI solutions, leveraging LLMs, knowledge graphs, and scalable AI workflows.

Key Responsibilities:

1. LangChain: Build modular, AI-powered applications with task automation.
2. LangGraph: Optimize knowledge graphs for real-time data inference.
3. Multi Agent Framework: Create and deploy multi-agent systems with dynamic tasking.
4. RAG Pipelines: Enhance generative AI with efficient retrieval systems and vector databases.
5. LLM Development: Fine-tune models using platforms like Hugging Face or TensorFlow.
6. Cloud Integration: Deploy scalable AI solutions on AWS, Azure, or GCP.
7. Optimization: Enhance performance, ensuring fairness, security, and privacy.

Qualifications:

1. Proficient in LangChain, LangGraph, Mukti, RAG, and vector databases (Pinecone, Weaviate).
2. Strong Python skills with hands-on experience in LLMs (GPT, BERT, LLAMA).
3. Familiar with cloud platforms and AI tools (AWS, Azure, GCP).

Preferred:

1. Experience with Hugging Face, Neo4j, and prompt engineering.

Soft Skills: Team player, quick learner, and passionate about emerging AI technologies.