Platform Engineer

Virtual Networx

St. Louis, MO, United States

1 day ago

Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Artificial Intelligence Ubuntu (Operating System) Performance Tuning Prometheus Azure Machine Learning Ceph (Software) Graphics Processing Unit (GPU) Data Storage Management Cloud Platform System Grafana Kubernetes Infrastructure Automation Frameworks

+3 more

Machine Learning Operations Hardware Infrastructure Terraform

Job description

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 o AI/ML platform operations o Reliability, performance, and cost optimization
Ensure smooth handoff of production systems with full operational readiness and support knowledge

Requirements

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