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# High-Performance Cloud Computing

- **Company:** DCM Infotech Limited
- **Location:** United States
- **Experience:** Experienced
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Cloud Computing, Continuous Integration, Software Debugging, Job Scheduling, Python (Programming Language), Azure Machine Learning, Google Cloud, Multi-Cloud, Kubernetes, Terraform, Oracle Cloud Infrastructure
- **Published:** October 15, 2026
- **Apply:** https://www.dice.com/job-detail/2a68abd0-3add-4ccc-9f95-158b0500ccad

## About the Role

* 10+ years in infrastructure engineering, cloud platforms, or HPC.
 * Kubernetes is the core requirement. You should have hands-on experience operating clusters at meaningful scale: node pool sizing, scheduler debugging, CNI troubleshooting, and rolling upgrades across large fleets. Candidates whose K8s experience is limited to small or local environments are unlikely to be a fit.
 * Terraform proficiency. You'll write and review infrastructure-as-code daily.
 * Working knowledge of AWS (EC2, S3, EFS, FSx for Lustre).
 * Python for tooling and automation.

Weighting client is applying to score candidates -

 * 4+ yrs Kubernetes at scale (CORE HPC experience nice to-have):
 * Python (tooling & automation):
 * Terraform:
 * GPU / HPC job scheduling:
 * Monitoring & incident response:
 * AWS (EC2, S3, EFS, FSx):
 * Multi-cloud K8s (Google Cloud Platform/CoreWeave)

## Description

* Operate Kubernetes platforms (EKS, CKS, GKE) at significant scale across providers. You're responsible for cluster lifecycle, node pool management, networking policy, and maintaining stability during rapid growth.
 * Provision HPC infrastructure through CI/CD system across AWS, CoreWeave, Google Cloud Platform, and OCI, with additional providers to be expanded in the near future.
 * Manage job scheduling to allocate GPU compute across training and inference workloads.
 * Define and maintain SLIs/SLOs. Build monitoring and alerting. Participate in severity escalation response and author post-incident reviews.
 * Coordinate daily with Networking, Storage, Security, and AI/ML platform teams.