DevOps Engineer (AI Inference)
HybridCyprus, Parish of Saint Ann, Jamaica
Job Summary
Design, develop, and maintain infrastructure for AI inference workloads, including GPU scheduling, model deployment pipelines, and data access patterns in on-prem environments. Build and manage monitoring and observability tools for AI inference platforms, including dashboards, alerts, and runbooks for model health and system performance. Collaborate with ML engineers and platform teams to design system architecture for AI workloads, integrate inference runtimes, and test performance at scale. Requires strong understanding of Kubernetes architecture, Linux troubleshooting, and automation using Python, Go, or Bash. Offers competitive compensation, flexible hybrid or remote options, and up to 45 days of work-from-anywhere time annually.
Required Qualifications
- Strong understanding of Kubernetes architecture, including CNI, CSI, operators, ingress/gateway, and control plane components.
- Hands-on experience operating and troubleshooting production Kubernetes clusters.
- Strong Linux and networking troubleshooting skills, including DNS, routing, firewalling, TLS, MTU, connectivity and performance issues.
- Ability to develop automation and operational tooling using Python, Go, or Bash.
- Experience with Terraform, Ansible, or similar IaC/configuration management tools.
- Experience with VictoriaMetrics/Grafana or similar monitoring, alerting, and troubleshooting tools.
- Strong experience with Git-based workflows and CI/CD pipelines.
- Familiarity with Cluster API or similar Kubernetes cluster lifecycle management technologies.
- Hands-on operation or administration of Slurm clusters.
- Knowledge of Argo CD, GitOps workflows, Helm, or Helmfile.
- Background working with managed platforms, PaaS, or cloud services.
- Exposure to bare metal, GPU, HPC, or other high-performance computing environments.
Desired Qualifications
- Familiarity with the NVIDIA GPU stack, RDMA/InfiniBand, or high-performance networking.
- Knowledge of OpenStack or similar cloud infrastructure platforms.
- Hands-on experience developing Kubernetes operators or controllers.
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