Autonomous AI agents are transforming industries by enabling systems to perform tasks, make decisions and adapt in real time without human intervention. In this talk, I will delve into the architecture and design principles required to build these agents within scalable AI infrastructure. Key topics will include constructing modular, reusable frameworks, optimizing resource allocation and enabling interoperability between agents and data pipelines. I will discuss practical use cases in which attendees will learn how to leverage containerization and orchestration techniques to enhance the flexibility and performance of these agents while ensuring low-latency decision-making. This session will also highlight challenges like ensuring robustness, ethical considerations and strategies for real-time feedback loops. Participants will gain actionable insights into building autonomous AI agents that drive efficiency, scalability and innovation in modern AI ecosystems.