Cloud Computing Engineer

Role: Cloud Computing Engineer
Location: Gondia, MH
Work Mode: Onsite
Employment Type: Full-Time
Roles & Responsibilities
Design, deploy, and manage scalable cloud infrastructure on Amazon Web Services (primary), with exposure to Microsoft Azure as a plus.
Work with core AWS services including:
Amazon EC2, Amazon EKS, Amazon S3, Amazon RDS
Networking via Amazon VPC, Elastic Load Balancing, Amazon Route 53
Security using AWS Identity and Access Management and AWS Secrets Manager
Manage and operate Kubernetes environments (EKS) with hands-on experience in Pods, Deployments, Services, Secrets, Ingress, and Persistent Volume Claims (PVC).
Deploy and manage open source and containerized applications using Helm, EC2, Docker and Kubernetes.
Build and maintain CI/CD pipelines using:
Jenkins, ArgoCD, Bitbucket
AWS native services such as AWS CodePipeline and AWS CodeBuild
Implement Infrastructure as Code (IaC) using Terraform or CloudFormation.
Implement monitoring, logging, and alerting using:
Prometheus, Grafana & Amazon CloudWatch
Troubleshoot production issues, perform root cause analysis, and ensure high availability and performance.
Optimize infrastructure for cost, scalability, and operational efficiency.
Required Skills
4+ years of hands-on experience with Amazon Web Services.
Strong understanding of cloud fundamentals: compute, storage, networking, IAM, and security best practices.
Hands-on experience with Kubernetes (Pods, Deployments, Services, Ingress, Secrets, PVC).
Experience with CI/CD tools (Jenkins / ArgoCD / Bitbucket / AWS CodePipeline) and Linux.
Experience with containerization using Docker and Kubernetes.
Experience with Infrastructure as Code using Terraform.
Monitoring and observability experience using Amazon CloudWatch, Prometheus and Grafana.
Scripting experience using Python/Bash for automation.
Good to Have
Experience with code quality and security tools like SonarQube and Snyk.
Experience with caching technologies such as Redis / Amazon ElastiCache.
Experience with Helm for Kubernetes deployments.
Exposure to multi-cloud environments (Azure preferred).
Preferred Skills
Experience with advanced observability platforms like Datadog
Exposure to aws services like Amazon SQS, EventBridge
Exposure to LLMOps tools and platforms (e.g., Arize Phoenix, Langfuse or similar)
Experience working in high-availability, production-grade environments
Understanding of DevSecOps practices and secure CI/CD pipelines

Work arrangement
No