Job Responsibilities:

Design, build, and maintain reliable, scalable, and secure cloud-native infrastructure platforms supporting large-scale production workloads.

Operate and optimize multi-account AWS environments, ensuring infrastructure is secure, repeatable, and auditable through Infrastructure as Code tools such as Terraform.

Manage production Kubernetes clusters, including provisioning, upgrades, autoscaling, networking, observability, capacity planning, and day-to-day operations.

Build and operate Kubernetes ecosystem components such as CRDs, Helm, HPA, Cluster Autoscaler, CoreDNS, and Cluster API.

Operate and improve GitOps-based deployment workflows using tools such as FluxCD or ArgoCD.

Manage and enhance Istio service mesh capabilities, including traffic routing, service discovery, resilience, security, and service-to-service communication.

Define and improve reliability practices, including SLOs, Error Budgets, monitoring, alerting, incident response, and post-mortems.

Participate in a scheduled on-call rotation to support production cloud infrastructure and Kubernetes platforms.

Troubleshoot complex production issues across cloud infrastructure, Kubernetes, Linux systems, networking, and distributed services.

Drive automation for infrastructure provisioning, configuration management, CI/CD pipelines, observability, and operational workflows using Terraform, Go, Python, or similar technologies.

Collaborate with application engineering, architecture, security, and platform teams to improve infrastructure reliability, scalability, and operational efficiency.

Job Requirements:

Bachelor’s degree or above in Computer Science, Software Engineering, Information Technology, or a related field.

2+ years of hands-on experience in cloud infrastructure, Kubernetes operations, platform engineering, SRE, or related areas.

Strong knowledge of AWS services, including EKS, IAM, VPC, EC2, S3, and related networking and security capabilities.

Hands-on experience operating Kubernetes in production environments, including cluster architecture, workload orchestration, networking, autoscaling, and troubleshooting.

Familiarity with Kubernetes ecosystem tools such as CRDs, Helm, Cluster API, HPA, Cluster Autoscaler, and CoreDNS.

Experience with GitOps tools such as FluxCD or ArgoCD.

Solid Linux administration and troubleshooting skills, including systemd, networking, and performance analysis.

Experience with CI/CD pipelines and infrastructure automation using Terraform, Go, Python, or similar tools.

Good understanding of reliability engineering practices, including SLOs, incident response, monitoring, alerting, and post-mortems.

Strong problem-solving skills and ability to diagnose and resolve complex infrastructure issues in distributed systems.

Willingness to participate in a scheduled on-call rotation.