Sr Domain\Technical Architect

HCL America, Inc.
United States
20 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$105,000.0 - $188,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Microsoft Azure Bash Shell Ubuntu (Operating System) Cloud Computing Continuous Integration Linux DevOps Domain Name System (DNS) Monitoring of Systems Linux System Administration Log Analysis
+19 more
Routing Role-Based Access Control Red Hat Enterprise Linux Ansible Prometheus TCP/IP AI Infrastructure Datadog Load Balancing Grafana Git Containerization Kubernetes Hardware Infrastructure Terraform Splunk Software Version Control Dynatrace Docker

Job description

We are seeking an experienced AI Factory Platform Operations Engineer to support deployment, operations, troubleshooting, and reliability of enterprise AI infrastructure. The role will focus on Linux-based infrastructure, Kubernetes and container platforms, networking, automation, monitoring, and operational support of AI/GPU environments. The engineer will work closely with infrastructure, network, DevOps, cloud, security, and engineering teams to maintain platform availability, resolve complex infrastructure issues, perform root cause analysis, and improve operational reliability., AI / GPU Infrastructure Operations Support day-to-day operations of AI infrastructure and GPU-based platforms. Perform infrastructure health checks

Requirements

Strong Linux administration: RHEL / Rocky Linux / Ubuntu Kubernetes administration and troubleshooting Docker / container runtime knowledge TCP/IP, DNS, routing, switching and load-balancing fundamentals Shell/Bash scripting Linux performance and log analysis Incident management and RCA Git/version control Infrastructure monitoring and troubleshooting The existing JD specifically calls for production Kubernetes experience including architecture, networking, storage, RBAC, pod lifecycle and cluster upgrades., AI Infrastructure / GPU platform exposure NVIDIA/GPU infrastructure concepts Prometheus / Grafana / Splunk / Datadog / Dynatrace Ansible / Terraform AWS / Azure / GCP CI/CD and DevOps practices Infrastructure-as-Code Experience working in large-scale production environments

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