Agentic AI Engineer

Key Responsibilities : Design and develop autonomous, goal-directed agent systems using LLMs, planning algorithms, and reinforcement learning. Integrate memory, tools, and feedback mechanisms into agentic workflows for continuous learning and adaptability. Implement multi-agent systems for collaborative task execution and coordination. Build and maintain toolchains and frameworks for agent planning, reasoning, execution, and monitoring. Collaborate with researchers and engineers to prototype and deploy agentic solutions in production. Ensure safety, explainability, and reliability of agentic AI systems. Stay current with advancements in autonomous AI, cognitive architectures, and agent frameworks (e.g., LangGraph, AutoGPT, CrewAI). Write clean, testable, and efficient code with appropriate documentation and design patterns. Required Qualifications : Bachelor’s or Master’s in Computer Science, Artificial Intelligence, or related field. 5–7 years of experience in AI / ML development, with at least 1–2 years focused on autonomous or agentic AI systems. Strong programming skills in Python (or similar), and experience with AI / ML frameworks such as PyTorch or TensorFlow. Experience with one or more of : LangChain, LangGraph, AutoGPT, ReAct, or similar agentic architectures. Solid understanding of LLMs, prompt engineering, and tool integration (APIs, plugins, retrieval-augmented generation). Familiarity with planning algorithms, reinforcement learning, or symbolic reasoning. Experience deploying scalable AI systems in cloud environments (AWS, GCP, or Azure)