AWS EKS / AI-ML Platform Engineer

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.

 

· 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.

· 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.

 

· 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.

· 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.

 

· 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.

· 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.

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

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.

· 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.

· 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.

· 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

· 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