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Senior Platform Engineer

STN Inc

Location
Hybrid (San Francisco Bay Area, California)
Employment
Full-time
Level
Senior Level
Posted 3 weeks ago

About the Role

STN Inc is seeking a Senior Platform Engineer to build and operate the multi-tenant orchestration and scheduling layer that transforms raw GPU infrastructure into a usable cloud service. This role is crucial for the company's GPU One (GPUaaS) offering.

Skills

Kubernetes Go Python GPU Infrastructure Infrastructure-as-Code Multi-tenancy API Design SRE Cloud Engineering Slurm Run:ai NVIDIA GPU Operator Service Mesh Istio Linkerd KubeRay

Perks

  • Remote OK

Full job details

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