Lead DevOps Engineer (AWS)

In this role, you will be responsible for operating and evolving a cloud-native, multi-tenant MLOps platform that supports machine learning and data science workloads. You will work closely with engineering, infrastructure, and data teams to ensure the platform remains secure, scalable, reliable, and continuously improving. Your work will directly contribute to enabling efficient AI/ML development and production environments across the organization.

Responsibilities

• Operate, maintain, and improve a Kubernetes-based MLOps platform
• Manage infrastructure using Terraform and GitOps practices
• Support tenant onboarding, platform services, deployment pipelines, and ML workflows
• Monitor platform health, respond to incidents, and improve operational processes
• Optimize platform performance, reliability, security, and cloud costs
• Collaborate with engineering, data science, and infrastructure teams to deliver a stable and scalable platform

• Experience with AWS services, including EKS, IAM, VPC, Route53, S3, ECR, and related cloud infrastructure
• Strong Kubernetes administration skills, including cluster operations, networking, autoscaling, and troubleshooting
• Hands-on experience with Infrastructure as Code using Terraform, Terragrunt, and Helm
• Experience with GitOps and CI/CD tools such as ArgoCD and GitHub Actions
• Knowledge of identity and access management, observability, and platform security best practices
• Experience with monitoring tools such as Prometheus, Grafana, CloudWatch, or Datadog
• Scripting and automation skills using Python and/or Bash
• Strong problem-solving skills and experience supporting production environments
• Excellent communication and collaboration skills
• Experience with NVIDIA technologies, including GPU infrastructure, GPU operators, CUDA, or AI/ML platform optimization (nice to have)