Senior Platform Engineer — AI Cloud Infrastructure

Senior Platform Engineer — AI Cloud Infrastructure

Location: San Francisco, CA — Onsite 5 days/week

Employment Type: Full-Time

Compensation: $220,000–$275,000 base + equity

Work Authorization: Candidates must be currently authorized to work in the United States. This position is not eligible for new or future employer-sponsored work authorization.

Note: No C2C arrangements will be considered.

Any attempt to use personal or household contact information for solicitation, candidate submission, or vendor outreach is strictly prohibited and will be reported to LinkedIn or other appropriate agencies.

About the Role

We are partnering with a well-funded AI company building a new GPU-focused cloud platform , and we're looking for a Senior Platform Engineer who wants to help build it from the ground up.

This is a true 0→1 infrastructure opportunity . You'll help design and build the systems that turn complex compute infrastructure into reliable, scalable, easy-to-consume cloud capacity.

The environment includes Kubernetes, Linux, Terraform, networking, storage, distributed systems, automation, observability, and GPU-accelerated compute .

Prior GPU or HPC experience is not required. If you've built strong production cloud or Kubernetes platforms and want to move deeper into AI infrastructure, we'd like to hear from you.

What You'll Do

• Design and build core infrastructure for a new AI/GPU cloud platform .
• Build and evolve production Kubernetes infrastructure for distributed and compute-intensive workloads.
• Develop platform tooling and infrastructure software using Python, Go, or similar languages .
• Build reusable infrastructure with Terraform / Infrastructure as Code .
• Automate provisioning, deployment, orchestration, scaling, and infrastructure lifecycle management .
• Create self-service platform capabilities that make infrastructure easier for engineers and customers to consume.
• Work across Linux, networking, storage, containers, cloud infrastructure, and distributed systems .
• Build observability and automation that make complex environments easier to operate and troubleshoot.
• Own meaningful infrastructure projects from design and architecture through production .
• Help establish technical direction while the platform is still being created.

What We're Looking For

• 5+ years of relevant platform, infrastructure, systems, SRE, or software engineering experience , or equivalent depth of experience.
• Strong hands-on experience with production Kubernetes .
• Strong Linux / systems fundamentals .
• Experience with Terraform or comparable Infrastructure-as-Code tooling .
• Professional programming or substantial infrastructure-development experience using Python, Go, or another systems-oriented language .
• Evidence that you've built or substantially extended infrastructure/platform capabilities , not only operated existing systems.
• Experience owning technical projects from architecture through production .
• Comfort solving problems across infrastructure boundaries and working in an environment where the answer isn't already defined.

Especially Valuable Experience

Any of the following is a plus — not a requirement :

GPU infrastructure • NVIDIA ecosystems • GPU scheduling • CUDA • NVIDIA GPU Operator • DGX • HPC • Slurm • Ray • InfiniBand • RDMA/RoCE • Bare metal • High-performance networking • Distributed storage • Kubernetes operators/controllers • Internal developer platforms • GitOps / ArgoCD • AI/ML infrastructure

Why This Opportunity

Most senior infrastructure roles ask you to inherit an established platform.

This one gives you the opportunity to help create one.

You'll join a small, highly technical team while fundamental decisions are still being made about compute provisioning, workload orchestration, Kubernetes, networking, storage, automation, reliability, and developer experience .

You'll have meaningful architectural influence while remaining deeply hands-on.

If you're a strong platform engineer who meets most of the core requirements but hasn't worked with GPU infrastructure yet, please apply. We care more about what you've built and how you think than whether you've already used every technology in the environment.