Generative AI Developer – LangChain, LangGraph, and RAG Expert
Generative AI Developer – LangChain, LangGraph, and RAG Expert
The Generative AI Developer will design and deploy cutting-edge AI solutions, leveraging LangChain, LangGraph, Multi Agent Framework, and Retrieval-Augmented Generation (RAG). Responsibilities include building AI-powered applications, optimizing knowledge graphs, creating multi-agent systems, enhancing generative AI with retrieval systems, and fine-tuning LLMs.
About the role
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
LangChain: Build modular, AI-powered applications with task automation.
LangGraph: Optimize knowledge graphs for real-time data inference.
Multi Agent Framework: Create and deploy multi-agent systems with dynamic tasking.
RAG Pipelines: Enhance generative AI with efficient retrieval systems and vector databases.
LLM Development: Fine-tune models using platforms like Hugging Face or TensorFlow.
Cloud Integration: Deploy scalable AI solutions on AWS, Azure, or GCP.
Optimization: Enhance performance, ensuring fairness, security, and privacy.
Qualifications
Proficient in LangChain, LangGraph, Mukti, RAG, and vector databases (Pinecone, Weaviate).
Strong Python skills with hands-on experience in LLMs (GPT, BERT, LLAMA).
Familiar with cloud platforms and AI tools (AWS, Azure, GCP).
Preferred
Experience with Hugging Face, Neo4j, and prompt engineering.
Soft Skills: Team player, quick learner, and passionate about emerging AI technologies.