Description

>> Lead the design, development, and deployment of advanced NLP and cognitive search solutions using Python, Langchain, LangGraph, Retrieval-Augmented Generation (RAG), and Agentic AI models.

>> Design scalable, maintainable AI solutions that integrate Langchain, LangGraph, and RAG methodologies to enhance knowledge discovery and conversational AI capabilities.

>> Develop and optimize RAG systems combining vector search, knowledge graphs, and LLMs to provide contextual and accurate responses.

>> Architect agentic AI systems that perform autonomous tasks by chaining actions, managing states, and integrating external APIs

. >> Create comprehensive technical documentation and architecture diagrams to facilitate knowledge transfer.

Requirements:

  >> 5-8+ years of exp.

>> Strong proficiency in Python, with experience in backend or AI service development.

>> Hands-on experience with Langchain and/or LangGraph frameworks.

>> Deep understanding of Retrieval-Augmented Generation (RAG) systems and techniques.

>> Experience designing and implementing agentic AI architectures, autonomous workflows, or multi-agent systems.

>> Familiarity with knowledge graphs, vector search engines (e.g., FAISS, Pinecone, Weaviate), and LLM integration.

>> Solid understanding of NLP concepts, transformer models, and prompt engineering.

>> Experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes)

Key Skills

Education

Bachelor's degree