Design and implement advanced LangGraph workflows with complex node logic, branching, and memory management.
Lead the development of agentic systems that interact, reason, and adapt dynamically.
Optimize performance and scalability of LangGraph graphs in production environments.
Integrate LangGraph with external APIs, databases, and LLMs to create seamless, intelligent pipelines.
Mentor junior developers and establish best practices for LangGraph development.
Collaborate with AI researchers and product teams to translate abstract ideas into robust LangGraph implementations.
Design , create and deploy AgenticAI models at production level.
Requirements:
Experience: 10 to 15 Yrs
Client is looking for - Hands on GenAI + LangGraph candidate assuming should be very good with GenAI Fundamentals, Prompt Engineering, LLM, Agentic AI, Agentic System Design, LangChain, LangGraph, Monitoring , CI/CD process. Coding expertise with using AI agent is very essential 10+ years in software engineering , with at least 2+ years in LangGraph or agentic frameworks .
Expert-level proficiency in Python , asynchronous programming, and graph-based computation.
Deep understanding of LLM orchestration , memory management, and stateful agent design.
Experience with LangChain, OpenAI, Anthropic, or similar LLM platforms .
Strong grasp of workflow debugging, graph visualization, and LangGraph Studio .
Proven ability to build production-grade agentic systems with high reliability and fault tolerance.
Proficient with AgenticAI models.
Vetted with Evaluation metrics(RAG, Batch processing, AgenticAI).