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STN Inc

Senior Platform Engineer

Posted Yesterday
Remote
Hiring Remotely in USA
Senior level
Remote
Hiring Remotely in USA
Senior level
Build and operate the multi-tenant platform layer for a GPU cloud service. Responsibilities include Kubernetes-based orchestration, tenant isolation, platform APIs and tools, GPU cluster automation, infrastructure as code, reliability and observability partnerships, customer issue support, environment templates, rollout tooling, architecture reviews, and reducing operational toil.
The summary above was generated by AI
Senior Platform Engineer

Platform and software · shared across customers

Reports to: Director, Platform Engineering (or Chief Architect)

Location: Remote (US) or Pleasanton, CA (hybrid)

Department: Cloud Platform Engineering / GPU Platform Engineering

Position summary

The Senior Platform Engineer builds and operates the multi-tenant orchestration, scheduling, and customer-facing platform layer that turns raw GPU infrastructure into a usable cloud service. This role is the software backbone of GPU One (GPUaaS).

Key responsibilities
  • Design and build the orchestration layer (Kubernetes, Slurm, Run:ai, or comparable)

  • Manage multi-tenant isolation including namespaces, networking, storage, and quotas

  • Build customer-facing platform APIs, CLIs, web portals, and SDKs

  • Implement and operate image management, GPU operator, and node provisioning automation

  • Drive infrastructure-as-code and automation across the platform stack

  • Partner with SRE on platform reliability, SLO definition, and observability

  • Support TAM and Support engineers on customer-impacting platform issues

  • Maintain customer environment templates, configuration management, and rollout tooling

  • Participate in architecture review, design discussions, and technical roadmap

  • Drive continuous platform improvement and reduce operational toil

Required qualifications
  • 6+ years in platform engineering, SRE, or cloud engineering at scale

  • Deep Kubernetes expertise including CRDs, operators, and multi-tenant patterns

  • Strong programming skills in Go, Python, or both

  • Experience operating GPU clusters or AI infrastructure at production scale

  • Bachelor's degree in computer science or equivalent experience

Preferred qualifications
  • Experience with NVIDIA GPU Operator, MIG, MPS, and NCCL operator patterns

  • Familiarity with Slurm operator, Run:ai, KubeRay, or comparable AI orchestration

  • Service mesh experience (Istio, Linkerd) and multi-cluster networking

  • Open source contributions in the cloud-native or AI infrastructure ecosystem

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