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Platform Engineer

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Onsite

Platform Engineer

AMroute LLC

Platform Engineer

Skills

GrafanaMachine LearningAIPrometheusLinuxKubernetesTerraform

3 months ago

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Important information


Contract type:

Permanent

Location:

St. Louis, MO, USA

Work mode:

Onsite

Published on:

9 August 2026

What they need


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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