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Engineered an AI-driven DevOps platform that enables self-healing infrastructure through closed-loop automation, enhancing system reliability. Integrated Dynatrace (Davis AI) for intelligent anomaly detection, root cause analysis, and alert correlation across microservices and Kubernetes environments. Developed over 20 Python automation scripts to streamline intelligent DevOps workflows, including environment version alignment and ArgoCD deployment automation, significantly reducing manual effort and configuration drift. Constructed event-driven automation workflows where Dynatrace alerts trigger Python-based agents for actions such as pod restarts, scaling, and service recovery. Implemented AI-driven Kubernetes observability to proactively identify pod failures, latency issues, and resource bottlenecks, improving system performance. Automated root cause analysis using log correlation and pattern recognition, decreasing manual debugging efforts by 40%. Achieved a 40% reduction in Mean Time to Resolution (MTTR) by integrating AI-powered monitoring with automated remediation pipelines. Established intelligent alerting and noise reduction using Dynatrace AI, enhancing operational efficiency and minimizing false positives.

Architected and managed multi-cloud infrastructure across AWS and Azure, facilitating scalable and highly available microservices platforms. Designed reusable and modular infrastructure patterns using Terraform, enabling consistent and rapid environment provisioning across multiple stages. Developed end-to-end CI/CD pipelines for microservices deployments, enhancing release frequency and minimizing deployment failures. Containerized applications using Docker and orchestrated workloads on Kubernetes AKS, ensuring high scalability and resilience. Implemented a GitOps-based deployment strategy using ArgoCD, ensuring version-controlled and automated Kubernetes application delivery. Integrated DevSecOps practices by embedding security scans (SonarQube, Trivy) into CI/CD pipelines to detect vulnerabilities early in the development process.

Managed and supported cloud-based infrastructure for banking and incident management applications, ensuring high availability and secure operations. Designed and maintained CI/CD pipelines to automate build, test, and deployment workflows, improving release efficiency and reducing manual intervention. Containerized applications using Docker and supported deployment of microservices-based architectures for scalable and resilient systems. Collaborated with development teams to ensure smooth application releases and consistency across development, testing, and production environments. Integrated DevOps practices into incident management workflows, enhancing issue tracking, resolution, and overall system reliability. Supported production systems by troubleshooting incidents, minimizing downtime, and improving overall application stability. Ensured application quality by integrating code quality and basic security checks, enhancing reliability and reducing defects in production.