Intelligent systems engineering is an interdisciplinary academic and professional field concerned with the principled design, development, deployment, and lifecycle management of complex systems that exhibit intelligent behavior. It integrates principles from artificial intelligence, computer science, and traditional engineering disciplines to create systems capable of learning, adaptation, reasoning, and autonomous decision-making in dynamic environments. As a research field, it investigates methodologies for architecting, implementing, verifying, and validating systems incorporating machine learning, reasoning engines, perception modules, and other AI components, exploring challenges such as robust design, uncertainty management, and human-system interaction. Its key characteristics include a focus on the entire system lifecycle, integration of heterogeneous components, rigorous verification for emergent behavior, and emphasis on scalability, reliability, and safety. The significance of intelligent systems engineering lies in enabling the creation of advanced autonomous agents and sophisticated decision support tools critical for addressing complex real-world problems across diverse domains.