We are seeking an experienced AWS EKS / AI-ML Platform Engineer to operate, maintain, support, and continuously improve a Kubernetes-based engineering AI/ML platform running on Amazon EKS.
The platform provides engineers and data scientists with an integrated environment for model development, training, workflow orchestration, distributed computing, and GPU/CPU-based workloads. The environment includes JupyterHub, Argo Workflows, Argo CD, Karpenter, Ray/KubeRay, Grafana, Prometheus, Loki, GitHub Actions, Amazon ECR, EFS, S3, RDS PostgreSQL, IAM/IRSA, KMS, and AWS networking/security services.
Key Responsibilities
EKS Platform Operations
· Operate and support the application/platform layer hosted on Amazon EKS.
· Manage Kubernetes namespaces, deployments, services, ingress, Helm releases, configuration, secrets, and platform services.
· Coordinate EKS/Kubernetes lifecycle changes with the AWS/Cloud Operations team.
· Troubleshoot pod scheduling, networking, storage, ingress, authentication, resource constraints, and application availability.
· Maintain platform reliability and operational readiness.
JupyterHub & User Workspace Management
· Administer JupyterHub/JupyterLab environments used by engineering and AI/ML users.
· Maintain user workspace configurations and container images.
· Troubleshoot notebook, pod, storage, image, authentication, and resource-allocation issues.
· Support CPU/GPU-based development and model-training workloads.
Workload Scheduling & Compute Management
· Manage Karpenter policies and Kubernetes compute provisioning.
· Support dynamic CPU/GPU node provisioning and workload scheduling.
· Monitor node utilization, pending workloads, scheduling failures, and capacity constraints.
· Tune resource requests/limits and platform policies to balance performance, reliability, and AWS cost.
AI/ML & Distributed Computing Platform
· Operate Argo Workflows for ML/data workflow orchestration.
· Support Ray/KubeRay distributed computing environments.
· Troubleshoot distributed workloads and worker provisioning.
· Support GPU workloads and associated NVIDIA Kubernetes components.
GitOps / CI-CD
· Administer Argo CD and GitOps-based application deployment.
· Maintain integrations with GitHub / GitHub Actions and Amazon ECR.
· Support controlled promotion of application/container changes across environments.
· Troubleshoot failed deployments, image pulls, Helm releases, sync failures, and configuration drift.
Monitoring & Observability
· Maintain Prometheus, Grafana and Loki monitoring/logging capabilities.
· Build operational dashboards and actionable alerts.
· Monitor:
o EKS cluster/platform health
o Pod and node health
o CPU/GPU utilization
o Memory utilization
o Workload queue/pending time
o Karpenter provisioning
o Failed workloads
o Application/service availability
o Storage utilization
· Support root-cause analysis for platform incidents.
AWS Service Integration
Operate and troubleshoot platform integrations involving:
· Amazon EKS
· Amazon ECR
· Amazon EFS
· Amazon S3
· Amazon RDS for PostgreSQL
· Application Load Balancer / AWS Load Balancer Controller
· Route 53
· AWS WAF
· AWS Certificate Manager
· IAM / IRSA
· AWS KMS
· AWS Systems Manager Parameter Store
· VPC endpoints / private connectivity
Platform Lifecycle & Upgrades
This should be a major responsibility of the role, rather than an incidental support activity.
· Own lifecycle management of platform Helm charts and application components.
· Plan, test, and execute platform upgrades.
· Track compatibility between EKS/Kubernetes and Karpenter, Argo, JupyterHub, KubeRay, Ray, PrometheGrafana and supporting components.
· Maintain upgrade runbooks and rollback procedures.
· Coordinate platform upgrades with AWS infrastructure teams and application owners.
Security & Access
· Support OIDC-based application authentication.
· Manage Kubernetes RBAC and IAM Roles for Service Accounts (IRSA).
· Maintain secrets and configuration securely.
· Support encryption and certificate management.
· Participate in vulnerability remediation and platform patching.
Production Support
· Provide operational support for platform incidents.
· Perform root-cause analysis and corrective actions.
· Develop operational runbooks and troubleshooting procedures.
· Automate repetitive administrative tasks.
· Work with Cloud Operations, application teams, engineering users, AWS, and other technology teams to resolve complex problems.
Required Technical Skills
· Strong hands-on Kubernetes / Amazon EKS administration
· AWS infrastructure knowledge
· Helm
· Argo CD
· Argo Workflows
· Karpenter
· JupyterHub / JupyterLab
· Kubernetes ingress and AWS Load Balancer Controller
· Prometheus / Grafana
· Git / GitHub and CI/CD
· Docker/container technologies
· Linux administration
· Kubernetes networking and storage
· IAM / IRSA
· ECR, EFS, S3
· Infrastructure troubleshooting
· Python and/or Bash automation
Experience Profile
Recommended level: Senior Platform Engineer / Lead Platform Engineer
I would target approximately:
· 7+ years infrastructure/platform/DevOps experience
· 3+ years hands-on Kubernetes experience
· 2+ years supporting production Amazon EKS environments
· Demonstrated experience operating production Kubernetes platforms rather than only deploying applications onto Kubernetes
