Senior DevOps Architect — Multi-Cloud Kubernetes Lead

EPAM Systems

Argentina

On-site

ARS 2,400,000 - 4,200,000

Full time

24 hours ago
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Benefits offered by this job

Healthcare benefits
Unlimited LinkedIn Learning access
Global career opportunities
Employee programs

Job summary

EPAM Systems in Argentina seeks a Lead DevOps Engineer to architect and operate a multi-cloud Kubernetes environment on AWS and Azure. You will implement GitOps with ArgoCD, manage IaC with Terraform and Helm, and ensure secure, scalable platform operations across regions.

You will lead a team with solid Kubernetes expertise, monitor systems with Prometheus/Grafana, and collaborate with development teams to optimize deployments and resource usage.

Qualifications

  • Five+ years of hands-on DevOps/engineering experience.
  • Proven leadership experience directing teams for 1+ year.
  • Strong English communication at B2+ level or above.
  • Deep Kubernetes, EKS/AKS, and multi-cloud experience with AWS and Azure.

Responsibilities

  • Architect, roll out, and oversee production-grade Kubernetes clusters across AWS and Azure.
  • Establish GitOps-driven workflows using ArgoCD and manage cluster configurations.
  • Build out infrastructure-as-code with Terraform and Helm/Helmfile for Kubernetes apps.
  • Monitor health with Prometheus, Grafana, and CloudWatch and set up alerting.

Skills

Cloud expertise
Leadership
English communication
GitOps

Education

Five+ years of DevOps/engineering experience

Tools

Kubernetes
EKS
AKS
ArgoCD
Argo Workflows
Argo Rollouts
Terraform
Helm
Helmfile
Prometheus
Grafana
CloudWatch

Job description

EPAM Systems in Argentina seeks a Lead DevOps Engineer to architect and operate a multi-cloud Kubernetes environment on AWS and Azure. You will implement GitOps with ArgoCD, manage IaC with Terraform and Helm, and ensure secure, scalable platform operations across regions.

You will lead a team with solid Kubernetes expertise, monitor systems with Prometheus/Grafana, and collaborate with development teams to optimize deployments and resource usage.

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