Hands on development using agentic AI frameworks such as LangGraph, LangChain, and other orchestration tools to build scalable agent based systems. Design and implement tool based workflows and integrations within the agentic AI ecosystem to support modular and reusable components. Develop and integrate with MCP clients to support external orchestration and control flows.

Build and maintain conversational AI bots with contextual understanding, memory, and agile tool invocation. Demonstrate expert level understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit learn) and how they integrate into agentic systems for inference, training, or feedback loops. Deep understanding of how LLMs are leveraged within agentic AI, including state management, handoffs between agents/tools, and interaction patterns in multi agent workflows.

Apply LLM Ops practices, including prompt engineering, versioning, performance monitoring, and observability in production environments.

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📌 Tech Lead - Machine Learning with Python (Hyderabad)
🏢 Tetrasoft
📍 Hyderabad