As AI becomes integral to modern applications, building robust and scalable AI platforms is crucial. This session explores communalities of AI and Platform Engineering, demonstrating how cloud native principles can be used to build AI platforms that are able to handle data-intensive workloads. We will show the unique challenges of AI systems—such as large-scale data management, complex model training cycles, and seamless deployment pipelines—and show how adopting proven platform engineering strategies can address these issues. Attendees will gain practical insights into automating AI workflows, ensuring system resilience, and integrating CNCF tools like Kubernetes, Kubeflow, and Argo Workflows to enhance AI capabilities within cloud-native environments.