Cloud Platform Engineer: AWS, Kubernetes & AI Orchestration

Linkedin; León; Presencial; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

LinkedIn is seeking a Cloud Engineer to lead the design, deployment, and operation of a Kubernetes-native, enterprise-grade AI agent orchestration platform on AWS. You will build scalable infrastructure, manage EKS clusters, and drive GitOps-based CI/CD pipelines across development, QA, and production environments.

The role requires hands-on AWS experience, Kubernetes expertise, and strong collaboration with platform and ML teams to ensure security, observability, and cost-efficiency.

Formación

• 4+ years of hands-on AWS experience
• AWS Solutions Architect certification (Associate or Professional)
• Proficient with EKS provisioning and operations
• Experience with Terraform-based infrastructure as code
• Kubernetes RBAC and network policies
• CI/CD pipelines for container workloads (GitHub Actions)
• GitOps workflows (ArgoCD/Flux)
• Observability tooling (Prometheus, Grafana, CloudWatch)
• Security controls (WAF, GuardDuty, Security Hub)
• SageMaker/Comprehend experience a plus

Responsabilidades

• Design, provision, and manage AWS infrastructure using Terraform
• Own end-to-end EKS clusters and node groups with Karpenter
• Implement CI/CD and GitOps pipelines (GitHub Actions, ArgoCD)
• Integrate security and compliance controls (GuardDuty, WAF, KMS)
• Maintain observability stack (CloudWatch, Managed Prometheus, Grafana)
• Collaborate with platform and ML teams for extensibility

Conocimientos

AWS

EKS

Terraform

Kubernetes

GitOps

CI/CD

ArgoCD

GitHub Actions

Security

Observability

Herramientas

Terraform

GitHub Actions

ArgoCD

Karpenter

OpenTelemetry

X-Ray

Descripción del empleo

LinkedIn is seeking a Cloud Engineer to lead the design, deployment, and operation of a Kubernetes-native, enterprise-grade AI agent orchestration platform on AWS. You will build scalable infrastructure, manage EKS clusters, and drive GitOps-based CI/CD pipelines across development, QA, and production environments.

The role requires hands-on AWS experience, Kubernetes expertise, and strong collaboration with platform and ML teams to ensure security, observability, and cost-efficiency.