Agentic AI Engineer

Key Responsibilities

• Design and develop Agentic AI applications using LangChain and LangGraph.
• Build autonomous and multi-agent workflows capable of planning, reasoning, memory management, and tool usage.
• Develop Retrieval-Augmented Generation (RAG) systems using vector databases.
• Integrate LLMs such as GPT, Claude, Gemini, Llama, and Mistral into enterprise applications.
• Create AI agents capable of interacting with APIs, databases, documents, and external tools.
• Implement agent memory, state management, and workflow orchestration using LangGraph.
• Create prompt engineering frameworks and optimize LLM performance.
• Develop evaluation, monitoring, and observability pipelines for AI agents.
• Deploy AI applications on cloud platforms and containerized environments.
• Collaborate with Data Scientists, ML Engineers, and Product Teams to deliver AI-powered solutions.
• Ensure security, scalability, and governance of AI systems.

Required Skills

• Agentic AI & LLM Frameworks
• LangChain
• LangGraph
• CrewAI
• AutoGen
• Semantic Kernel
• LlamaIndex