Senior AI Infrastructure Engineer/AI Platform Engineer

About the role

Lead enterprise infrastructure initiatives supporting Generative AI and Predictive AI platforms.

Tasks

• Design, deploy, and operate scalable AI/ML infrastructure supporting model training, inference, and batch workloads.
• Build and manage GPU-enabled Kubernetes/OpenShift platforms and large-scale, multi-node GPU clusters.
• Support GPU scheduling, resource allocation, quota management, capacity planning, and performance optimization.
• Implement monitoring, observability, and alerting using Grafana, Splunk, and enterprise telemetry tools.
• Define SLIs/SLOs, improve platform reliability, and proactively identify performance and capacity risks.
• Develop AI-driven automation and AIOps solutions for self-healing, intelligent diagnostics, scaling, and incident remediation.
• Lead production incident management, root-cause analysis, and continuous reliability improvements.
• Support highly available infrastructure, business continuity, and disaster recovery in regulated enterprise environments.

Requirements

• 5+ years of infrastructure engineering experience.
• 5+ years of Linux systems administration and complex end-to-end troubleshooting.
• 4+ years of Kubernetes/container platform experience, including production support.
• 4+ years of AI/ML platform infrastructure and operations experience.
• Hands-on experience with Kubernetes and preferably Red Hat OpenShift.
• Experience with GPU-enabled infrastructure, scheduling, utilization monitoring, and performance tuning.
• Strong monitoring and observabi

Schedule

• Duration: 1 Year

Location

• Charlotte, NC
• Chandler, AZ
• Dallas, TX
• Iselin, NJ
• Local candidates only for the listed locations.