Abstract : Cloud-native architectures have revolutionized deployment agility and scalability, but introduce fragility through distributed failure domains, tight service dependencies, and configuration complexity. This paper presents a real-world case study in transforming a multi-tier enterprise platform suffering from chronic outages into a zero-downtime, resilient infrastructure using Site Reliability Engineering (SRE) principles. To solve these challenges‚ we innovated on four key pillars with SRE leading the charge: AI augmented reliability automations like anomaly detection and AIOps-based incident triage‚ autonomous recoverability with canary deployments‚ Argo Rollouts progressive delivery and multi-region failover orchestration‚ chaos engineering with AWS Fault Injection Simulator (FIS)‚ LitmusChaos and Steadybit for failure injection testing‚ GitOps-powered policy-as-code with ArgoCD and Open Policy Agent (OPA) which provided Compliance as Code and automated configuration drift detection across the stack? The transformation also included an Embedded SRE model where reliability engineering was embedded in the product teams? Detailed metrics show that during nine months of operating the transformed platform‚ MTTR improved from 120 minutes to 11 minutes‚ there were no unplanned outages in four fiscal quarters‚ Priority 1 (P1) incidents decreased by 65%‚ and developer deployment frequency increased by three times? This case study provides a validated, replicable SRE transformation blueprint for enterprises operating cloud-native multi-tier architectures at production scale