STN Inc Jobs

Senior Platform Engineer

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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