Tech Leader with 17+ years of expertise in architecting and delivering mission-critical, cloud-agnostic, scalable applications using microservices and event-driven architectures. Experienced across the Railroad, Healthcare, Logistics, and Energy industries, with a proven track record of leading engineering teams to deliver mission-critical applications successfully. Pioneer the adoption of new technologies and frameworks, enabling teams to adopt modern solutions and AI-assisted development faster and improve productivity. Currently, I’m leading multiple teams at Wabtec to deliver the Precision Dispatch System that drives operational efficiency, reliability, and safety in the railroad industry.

Title: From Cloud-Native to AI-Native: Reimagining Enterprise Software Architecture for the Next Decade - Abstract: The rapid advancement of Artificial Intelligence is fundamentally transforming how software systems are designed, built, deployed, and operated. While cloud-native architectures revolutionized scalability, resilience, and agility over the past decade, organizations are now entering a new era where software must be designed as AI-native from inception. This presentation explores the architectural principles, engineering practices, and organizational shifts required to build intelligent software systems at enterprise scale. Drawing upon industry experiences and emerging technology trends, the session examines how modern platforms are evolving to incorporate large language models, AI-powered development tools, intelligent automation, and real-time decision-making capabilities. Attendees will gain insights into key architectural considerations including data-centric design, AI service integration patterns, model lifecycle management, observability, governance, security, and operational resilience. The presentation will also discuss how platform engineering, cloud-native technologies, and DevSecOps practices provide the foundation for reliable AI-enabled applications. Beyond technology, the session addresses the practical challenges organizations face when transitioning from experimental AI initiatives to production-grade enterprise solutions. Particular emphasis will be placed on balancing innovation with responsible AI practices, ensuring scalability while managing risk, and aligning technical transformation with business objectives. By the end of the session, participants will understand how software architecture is evolving in response to AI-driven requirements and will be equipped with actionable strategies for building future-ready systems. The presentation offers a pragmatic perspective on how engineering leaders and architects can successfully navigate the transition from cloud-native to AI-native enterprises while maintaining reliability, governance, and long-term architectural sustainability.