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Platform Engineer

Job in St. Louis, Saint Louis, St. Louis city, Missouri, 63105, USA
Listing for: AMroute LLC
Full Time position
Listed on 2026-08-15
Job specializations:
  • IT/Tech
    Systems Engineer, SRE/Site Reliability, Cloud Computing: Infrastructure & Operations
Job Description & How to Apply Below
Location: St. Louis

Job Title :
Platform Engineer Note : US Citizen or Green Card candidates Duration : 160 hours

Location:

St. Louis, MO

100% Onsite

Role Overview

Highly skilled AI Infrastructure Engineer to design, build, and operate scalable GPU-enabled Kubernetes platforms for AI/ML workloads.

Job Title :
Platform Engineer Note : US Citizen or Green Card candidates Duration : 160 hours

Location:

St. Louis, MO

100% Onsite

Role Overview

Highly skilled AI Infrastructure Engineer to design, build, and operate scalable GPU-enabled Kubernetes platforms for AI/ML workloads.

Must have skills:

Kubernetes, Linux, Terraform, GPUs and NVIDIA stack

Required Qualifications
  • 3-8+ years' experience
  • Strong Kubernetes knowledge
  • Experience with GPUs and NVIDIA stack
  • Linux (Ubuntu) expertise
  • Experience with Terraform
Preferred Qualifications
  • Longhorn or Ceph experience
  • Canonical ecosystem (MAAS, Juju)
  • AI/ML tools like Kubeflow
  • Certifications (CKA, NVIDIA)
Soft Skills
  • Strong problem-solving and troubleshooting mindset
  • Ability to collaborate with cross-functional teams (ML engineers, data scientists)
  • Clear communication and documentation skills
  • Passion for automation and platform scalability
Key Responsibilities
  • Design and manage Kubernetes clusters
  • Build GPU-enabled infrastructure
  • Deploy Longhorn storage
  • Automate infrastructure using Terraform
  • Monitor systems using Prometheus and Grafana
  • Knowledge Transfer & Client Enablement
  • Provide structured knowledge transfer (KT) sessions to client teams on all core platform components, including:
    • Kubernetes architecture, operations, and troubleshooting
    • GPU infrastructure (NVIDIA stack, scheduling, resource optimization)
    • Longhorn storage management and performance tuning
    • Canonical ecosystem tools (MAAS, Juju, Charmed Kubernetes)
  • Develop and deliver technical documentation, runbooks, and training materials to support ongoing operations
  • Conduct hands‑on workshops and guided sessions to enable client teams to independently manage and scale the platform
  • Act as a technical advisor, helping client stakeholders understand best practices in:
    • Cloud‑native infrastructure
    • AI/ML platform operations
    • Reliability, performance, and cost optimization
  • Ensure smooth handoff of production systems with full operational readiness and support knowledge
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