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# AWS EKS / AI-ML Platform Engineer

- **Company:** IT Solutions
- **Location:** United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Microsoft Access, Artificial Intelligence, Amazon Web Services, Amazon S3, Component-Based Software Engineering, User Authentication, Bash Shell, Cloud Computing, Continuous Integration, DevOps, Distributed Systems, Github, Monitoring of Systems, Identity and Access Management, Python (Programming Language), Key Management, PostgreSQL, Linux System Administration, Machine Learning, Octopus Deploy, OpenID, Role-Based Access Control, Prometheus, Azure Machine Learning, Runbook, Software Deployment, Software Vulnerability Management, Workflow Management Systems, SSL Certificate Management, Data Logging, Graphics Processing Unit (GPU), Load Balancing, System Availability, Grafana, Kubernetes Helm Charts, Amazon Virtual Private Cloud (VPC), Amazon Relational Database Service, Containerization, Kubernetes, Enterprise Integration, Route53, AWS EKS, Docker
- **Published:** November 7, 2026
- **Apply:** https://www.dice.com/job-detail/d37bce71-e875-4ac3-a5af-9b6962cb74b9

## About the Role

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

## Description

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., · 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.

 2. 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.

 3. 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.

 4. 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.

 5. 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.

 6. 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.

 7. 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

 8. 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.

 9. 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.

 10. 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., · 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