Cloud Engineer(Argocd , Prometheus , Flink , Kafka, Kubernetes, Terraform,Ci/Cd)

Key Responsibilities Design, deploy, and manage cloud infrastructure using AWS services while ensuring high availability and scalability. Build, administer, and optimize Kubernetes clusters for containerized applications in production environments. Develop and maintain Infrastructure as Code using Terraform for automated infrastructure provisioning and lifecycle management. Design, implement, and enhance CI/CD pipelines to streamline software delivery and deployment automation. Develop automation scripts using Python to improve operational efficiency and reduce manual effort. Monitor infrastructure, applications, and cloud services to ensure platform reliability and performance. Perform production incident management, root cause analysis, and implement preventive measures. Collaborate with development, security, and operations teams to improve platform reliability and deployment processes. Implement cloud security best practices, secrets management, and infrastructure automation. Optimize cloud resources, system performance, and operational costs across enterprise environments. Maintain technical documentation, operational runbooks, and deployment standards. Support on-call operations and contribute to continuous platform improvements. Requirements 7+ years of experience in Site Reliability Engineering, Platform Engineering, or DevOps. Strong hands-on experience with AWS cloud services and cloud infrastructure management. Extensive experience managing Kubernetes environments and containerized workloads. Experience in Infrastructure as Code using Terraform. Strong experience building enterprise CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, ArgoCD, or similar tools. Hands on experience in Azure, OpenStack Proficiency in Python scripting for automation and infrastructure management. Experience with Docker, Linux administration, and cloud networking. Experience in monitoring, troubleshooting, and optimizing Flink applications in production environments. Hands-on experience with monitoring and observability tools such as Prometheus, Grafana, ELK/OpenSearch, and CloudWatch. Experience in DevSecOps practices, security automation, and configuration management. Strong troubleshooting, analytical, and production support skills. Experience working in Agile environments using Jira and Confluence. Experience in distributed data processing, stream analytics, and integration with messaging platforms such as Kafka. Preferred AWS Certifications or Kubernetes certifications. Experience with OpenShift, Rancher, or cloud-native technologies. Knowledge of AI/ML infrastructure or MLOps platforms. Experience with enterprise-scale production support and high-availability systems.