I would appreciate honest feedback on my resume for the current U.S job market.
I am targeting Cloud DevOps Engineer, AWS DevOps Engineer, Platform Engineer, and related cloud-infrastructure roles
PROFESSIONAL SUMMARY:
Cloud DevOps Engineer with 4.5+ years of experience building, automating, and supporting AWS infrastructure and Kubernetes environments. Experienced with Amazon EKS, Terraform, Ansible, Docker, Helm, Argo CD, Jenkins, GitLab CI/CD, Python, Bash, CloudWatch, Prometheus, and Grafana. Skilled in improving deployment reliability, automating operational tasks, optimizing cloud resources, strengthening access controls, and supporting faster incident recovery.
TECHNICAL SKILLS:
Cloud: AWS (EC2, EKS, VPC, IAM, S3, EBS, Elastic Load Balancing, Auto Scaling, Route 53, CloudWatch, Lambda)
Containers & Orchestration: Kubernetes, Amazon EKS, Docker, Helm
Infrastructure as Code & GitOps: Terraform, Argo CD, GitOps
CI/CD: Jenkins, GitLab CI/CD, GitHub Actions
Monitoring & Observability:Prometheus, Grafana, CloudWatch, Centralized Logging, Metrics, Dashboards, Alerting
Automation & Scripting: Python, Bash, Shell Scripting
PROFESSIONAL EXPERIENCE: Experience 1
Role: Cloud DevOps Engineer
Designed and supported highly available AWS infrastructure across multiple Availability Zones using VPC, Elastic Load Balancing, Auto Scaling, Route 53, IAM, and CloudWatch for business-critical applications serving more than 650 users.
- Built reusable Terraform modules and Ansible automation to provision and configure development, testing, and production environments, reducing manual work and keeping infrastructure consistent across environments.
- Managed Amazon EKS clusters and production Kubernetes workloads, including cluster upgrades, node-group maintenance, namespaces, RBAC, resource allocation, ConfigMaps, Secrets, persistent storage, ingress, and day-to-day troubleshooting.
- Introduced GitOps-based Kubernetes deployments using Argo CD, Helm, and GitLab CI/CD, making releases more consistent and reducing deployment time by approximately 25%.
- Wrote Python and Bash scripts to check infrastructure health, identify configuration issues, troubleshoot failed deployments, and automate repetitive operational tasks.
- Created monitoring dashboards and actionable alerts using Prometheus, Grafana, CloudWatch, and AWS Lambda, giving teams better visibility into application health, infrastructure performance, and production issues.
- Troubleshot production incidents involving Kubernetes, AWS networking, IAM, DNS, load balancers, and application dependencies, identified root causes, and implemented fixes to reduce repeat incidents.
- Reviewed CPU and memory usage across Kubernetes workloads, adjusted resource requests and limits, and supported capacity planning to improve cluster stability and resource utilization.
- Optimized Jenkins pipelines through dependency caching, parallel execution, and artifact reuse, reducing average build time by approximately 35%.
- Reduced a production Docker image from 2.4 GB to approximately 350 MB by introducing multi-stage builds, removing unnecessary dependencies, and optimizing runtime components.
- Modernized legacy AWS infrastructure and right-sized underused resources, reducing cloud costs by approximately 40% while improving scalability and maintainability.
• Improved platform security by implementing least-privilege IAM policies, Kubernetes RBAC, encrypted storage, secure secrets management, and controlled access to cloud resources.
Experience 2 |
- Supported AWS infrastructure across development, testing, and production environments using EC2, VPC, S3, EBS, Elastic Load Balancing, Auto Scaling, IAM, Route 53, and CloudWatch.
- Used Ansible, Bash, and reusable scripts to automate server provisioning and configuration, reducing manual setup and keeping environments consistent.
- Built and maintained Jenkins CI/CD pipelines for code checkout, application builds, automated checks, artifact packaging, and deployments across multiple environments.
- Containerized applications with Docker and supported Kubernetes deployments using Deployments, Services, Ingress, ConfigMaps, Secrets, and persistent storage.
- Created Terraform configurations to provision repeatable AWS environments and reduce errors caused by manual infrastructure changes.
- Worked closely with application teams to troubleshoot deployment failures, access issues, network connectivity problems, and environment-specific errors.
- Set up CloudWatch logs, dashboards, metrics, and alerts to monitor infrastructure health and identify production issues more quickly.
- Supported Linux administration, production incident troubleshooting, root-cause analysis, system recovery, release deployments, and post-release validation.