Platform Engineer: AI Infra on Multi-Cloud Kubernetes

Reactor; San Francisco (CA); On-site; USD 190,000 - 260,000; Full time

Benefits offered by this job

Visa sponsorship

Relocation assistance

Health, dental, vision

Equity

Job summary

Reactor in San Francisco is seeking an infrastructure lead to own the platform our AI models run on. You’ll manage multi-region Kubernetes clusters across cloud providers, implement IaC, and drive GPU orchestration for fast, reliable model serving.

You’ll build a robust observability and networking stack, own security and CI/CD for Go and Python services, and partner with ML engineers to optimize containerized workloads in a high-growth startup.

Qualifications

• Experience operating Kubernetes at production scale, including node-level debugging and upgrades.
• Proficient with infrastructure-as-code across environments and regions.
• Experience with GPU workloads on Kubernetes and GPU-aware scheduling.

Responsibilities

• Provision and manage multi-region Kubernetes clusters across AWS and GPU clouds using IaC.
• Own the GitOps deployment lifecycle (Helm, Kustomize, image automation, CD).
• Manage GPU node infrastructure: scheduling, caching, prefetching, observability.

Skills

Kubernetes at scale

Infrastructure as code

GPU workloads on Kubernetes

GitOps tooling

Helm chart authoring

Observability stack

Networking fundamentals

End-to-end infra ownership

Go or Python proficiency

Container orchestration

Tools

Terraform

Pulumi

FluxCD

ArgoCD

Kustomize

Helm

Redis

Job description

Reactor in San Francisco is seeking an infrastructure lead to own the platform our AI models run on. You’ll manage multi-region Kubernetes clusters across cloud providers, implement IaC, and drive GPU orchestration for fast, reliable model serving.

You’ll build a robust observability and networking stack, own security and CI/CD for Go and Python services, and partner with ML engineers to optimize containerized workloads in a high-growth startup.