Work
Experience:
13–15 Years (including 4+Years in a lead role)
Requirements:
Mandatory Skills:
Strong hands-on experience in Kubernetes cluster management, administration, scaling, and troubleshooting.
AWS Bedrock
Strong experience in managing AWS EKS and Azure AKS production clusters.
Strong experience in Kubernetes upgrades, patching, node management, autoscaling, ingress, storage, networking, RBAC, and secrets management.
Working experience with Azure or private cloud environments.
Strong hands-on experience with Terraform for infrastructure provisioning and automation.
Hands-on experience in AWS Bedrock or exposure to AI/GenAI platform services is preferred.
Experience supporting AI/ML or GenAI workloads on cloud platforms is an added advantage.
Experience in Terraform modules, remote backend, state management, workspaces, variables, outputs, and environment-based deployments.
Hands-on experience with CI/CD tools such as Jenkins, GitHub Actions, or Azure DevOps.
Experience in designing and maintaining CI/CD pipelines for application and infrastructure deployments.
Strong automation and scripting skills using Bash, Shell, and Python.
Strong understanding of cloud security, IAM, RBAC, compliance, governance, encryption, secrets management, and network security.
Desired Skills:
CKA certification, AWS Solutions Architect or AWS DevOps Engineer certification.
Azure Administrator or Azure Solutions Architect certification.
Experience with multi-cloud environments including AWS, Azure, and private cloud.
Hands-on experience with Helm charts, Kustomize, and Kubernetes operators.
Experience with Kubernetes add-ons such as Karpenter, Cluster Autoscaler, External DNS, Cert Manager, CSI drivers, Metrics Server, and Ingress Controllers.
Experience in cloud cost optimization, tagging governance, budget alerts, and FinOps reporting.
Exposure to AWS Bedrock or AI/ML platform services is an added advantage.
Exposure to MLOps tools such as MLflow, model registry, feature store, or AI workload operations is good to have.
Experience with configuration management tools such as Ansible, Chef, Puppet, or similar platforms.
Qualifications:
Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
Job Description:
Design, build, and manage scalable platform engineering solutions across AWS, Azure, and Kubernetes environments.
Lead implementation and operations of Kubernetes platforms such as EKS, AKS, and other container orchestration platforms.
Define platform standards, reusable templates, golden paths, and self-service capabilities for application teams.
Build and maintain CI/CD and GitOps-driven deployment models using Jenkins, GitHub Actions, GitLab CI, Azure DevOps, Argo CD, or Flux.
Develop and manage Infrastructure as Code using Terraform modules, remote state, reusable patterns, and environment-based deployments.
Drive Kubernetes best practices for RBAC, namespaces, secrets, ingress, autoscaling, storage, networking, security, and upgrades.
Improve developer productivity by creating standardized deployment workflows and automation frameworks.
Implement observability, logging, monitoring, and alerting for cloud-native platforms.
Ensure high availability, scalability, reliability, security, and cost optimization of platform services.
Troubleshoot complex Kubernetes, cloud, CI/CD, networking, and infrastructure issues.
Define DevSecOps practices including image scanning, code scanning, vulnerability management, secrets management, and policy enforcement.
Collaborate with development, security, infrastructure, architecture, and operations teams.
Mentor junior and mid-level engineers on Kubernetes, cloud, Terraform, CI/CD, and platform engineering best practices.
Support AI/ML and GenAI platform requirements, including AWS Bedrock exposure where applicable.
Drive continuous improvement in automation, reliability, operational maturity, and platform adoption.