Senior Agentic AI Infrastructure Engineer I - Core Platforms

What you'll do

• Design and operate GPU- and accelerator-enabled platforms, including scheduling, capacity management, and utilization optimization.
• Build reusable infrastructure for AI training, inference, and agentic workloads; improve observability, reliability, security, and cost management.
• Lead cross-functional infrastructure projects, resolve complex issues, and mentor engineers.

What they ask for

• 5+ years in infrastructure engineering, cloud engineering, DevOps, or a related technical field, including at least 2 years supporting AI-enabled infrastructure, AI automation, or agentic AI technologies.
• Experience with Kubernetes-based AI platforms, containers, workload schedulers, and GPU or accelerator orchestration in cloud or hybrid environments.
• Experience operating model-serving or inference platforms and optimizing production AI workloads.
• Bachelor's degree in Computer Science, Information Technology, Engineering, and/or comparable experience.

Nice to have

• Advanced degree preferred.
• Experience with agent frameworks such as LangGraph or Semantic Kernel.

Pay

$123000 - $215250 annually (base salary)

Tools

LangGraph, Semantic Kernel, Kubernetes, Ansible, Puppet, Terraform, Python, Prometheus

AI focus

Builds and operates infrastructure for agentic and AI-enabled workloads, including GPU/TPU platforms, model training and inference, AIOps, AI-assisted automation and observability, and human-reviewed AI operational workflows.