DevOps & Platform Engineer
Five years building and running production infrastructure on AWS: Kubernetes on EKS, Terraform, and CI/CD.
I build CI/CD pipelines with GitHub Actions and Jenkins, operate EKS clusters, and automate infrastructure with Terraform and Helm. Security is part of the daily work: least-privilege IAM, Kubernetes RBAC, Secrets Manager, and TLS across all environments. I monitor with Prometheus and Grafana, keep cloud costs in check, and use AI tooling (GitHub Copilot, Claude Code, MCP integrations) in real infrastructure workflows.
5+
Years in Production
30%
Cloud Cost Reduction
50%
Faster Deployments
Core Expertise
Platform & DevOps Engineering
EKS cluster operations and Terraform-based infrastructure with GitOps delivery through
GitHub Actions. Helm for workload packaging, Argo CD and Argo Rollouts for blue/green
and canary releases on high-traffic services.
Security & Observability
Least-privilege IAM, Kubernetes RBAC, AWS Secrets Manager with External Secrets, TLS
everywhere, and WAF in front of public endpoints. Monitoring with Prometheus, Grafana,
and Datadog, plus on-call incident response on the SEV team, triaging and resolving
SEV-1 and SEV-3 production incidents across internal and external applications.
AI-Assisted Engineering
GitHub Copilot and Claude Code in day-to-day development, plus custom MCP integrations
for troubleshooting and documentation. AI tooling applied to real infrastructure work,
with a human reviewing every change.
Projects
EKS Autoscaling & Progressive Delivery
Problem
Node scaling driven by CloudWatch alarms could not keep up with heavy workloads.
Pods sat in Pending while capacity caught up, and releases to high-traffic
services carried real risk.
What I Built
Replaced CloudWatch-based node scaling with Cluster Autoscaler on EKS. Set up
blue/green and canary deployments for high-traffic services, and automated the
release path with GitHub Actions, AWS ECR, and Helm. Migrated single-instance RDS
databases to Aurora PostgreSQL multi-AZ for higher availability and automated
backups. Infrastructure changes go through Terraform modules and GitOps, not
manual steps.
Outcome: pending-pod issues resolved, fewer failed releases, a multi-AZ database
tier with automated backups, and canary or blue/green as the default path for
high-traffic services.
3-Tier Service Review System on AWS
Problem
Environments were built by hand: slow, inconsistent, and drifting apart between
dev, stage, and prod. Frontend and backend deployments were manual and
error-prone.
What I Built
Reusable Terraform modules for the full stack (VPC, ALB, Auto Scaling, RDS, S3),
so any environment can be rebuilt from code. Jenkins CI/CD pipelines for frontend
and backend services.
80%
less manual
build time
build time
50%
faster
deployments
deployments
0
environment
drift
drift
Monitoring Migration & Cloud Cost Reduction
Problem
Datadog licensing costs grew with the fleet, and the AWS bill carried obvious
waste: oversized instances and autoscaling groups that were never tuned.
What I Built
Migrated monitoring from Datadog to Prometheus and Grafana on EKS using custom
Helm charts. Rightsized AWS resources and tuned ASG autoscaling policies across
environments.
30%
monthly AWS
cost reduction
cost reduction
2→1
monitoring stacks
after migration
after migration
Technical Depth
AWS
EC2, S3, RDS, Aurora PostgreSQL, VPC, ALB, Lambda, API Gateway, ECR, CloudFormation, CloudWatch, SSM, WAF, cost optimization
Kubernetes
EKS, Docker, Helm, Argo CD, Argo Rollouts, Cluster Autoscaler, HPA, RBAC, External Secrets, network policies
IaC & CI/CD
Terraform, Terraform Cloud, CloudFormation, Ansible, GitHub Actions, Jenkins, Git
Observability
Prometheus, Grafana, Datadog, Kibana, CloudWatch, alerting and production troubleshooting
Security
IAM least-privilege, Kubernetes RBAC, AWS Secrets Manager, External Secrets, TLS, WAF
Scripting & AI
Python, Bash, SQL, Java, Linux, GitHub Copilot, Claude Code, MCP integrations