HPC — AWS Consultant Work Mode: Remote Role Overview We are looking for an experienced HPC — AWS Consultant with strong expertise in Kubernetes, cloud infrastructure, and infrastructure automation to support large-scale High-Performance Computing (HPC) environments. The role involves operating and scaling multi-cloud Kubernetes platforms supporting GPU-intensive AI research, model training, and production inference workloads. The ideal candidate should have hands-on experience managing Kubernetes clusters at scale, provisioning cloud infrastructure using Terraform, and troubleshooting complex infrastructure and networking issues. Tech Stack Cloud Platforms: AWS, CoreWeave, GCP, OCI Kubernetes: Amazon EKS, CKS, GKE Infrastructure as Code: Terraform AWS Services: EC2, S3, EFS, FSx for Lustre HPC Scheduling: Slurm Programming & Automation: Python CI/CD: Infrastructure provisioning and deployment pipelines Monitoring: SLIs, SLOs, Monitoring & Alerting Container Networking: CNI, Kubernetes Networking Policies

Key Responsibilities

Operate and maintain large-scale Kubernetes platforms across AWS, CoreWeave, GCP, and other cloud providers. Manage cluster lifecycle, node pool sizing, networking policies, scheduler configurations, and rolling upgrades. Provision and manage HPC infrastructure through CI/CD pipelines. Manage Slurm-based job scheduling to efficiently allocate GPU compute resources across AI training and inference workloads. Troubleshoot Kubernetes networking, CNI, scheduler, and infrastructure-level issues. Develop and maintain infrastructure automation using Terraform and Python. Define and maintain SLIs/SLOs, monitoring systems, and alerting mechanisms. Participate in incident response, troubleshoot critical infrastructure failures, and prepare post-incident reviews. Collaborate with Networking, Storage, Security, and AI/ML Platform teams. Required Skills & Qualifications 4+ years of experience in Infrastructure Engineering, Cloud Platforms, DevOps, or HPC environments. Strong hands-on experience operating Kubernetes clusters at production scale. Experience with Kubernetes node pool management, scheduler debugging, CNI troubleshooting, and rolling upgrades. Proficiency in Terraform and Infrastructure as Code (IaC). Working knowledge of AWS services, particularly EC2, S3, EFS, and FSx for Lustre. Strong Python scripting and automation skills. Experience managing cloud infrastructure and troubleshooting complex distributed systems. Understanding of monitoring, alerting, incident management, and infrastructure reliability.

Preferred Qualifications

Hands-on experience with Slurm workload and GPU job scheduling. Experience managing GPU-intensive infrastructure for AI/ML workloads. Exposure to CoreWeave, GCP, or Oracle Cloud Infrastructure (OCI). Experience with high-performance computing (HPC) environments. Knowledge of Kubernetes networking, storage integration, and multi-cloud architecture. Experience working with large-scale GPU clusters.

Work Environment

Remote-first working environment. Occasional on-site visits to customer offices may be required. Company laptop provided. Opportunity to work on large-scale, multi-cloud HPC infrastructure supporting advanced AI workloads. Important Candidate Requirement Kubernetes expertise is the primary selection criterion. Candidates must have practical experience operating and troubleshooting production Kubernetes clusters at meaningful scale. Experience limited to small-scale, local, or basic Kubernetes deployments will not be sufficient.