Location: San Francisco, CA preferred (remote currently)

Work Model: Remote

Industry: AI infrastructure

Compensation: $180K-$250K base, plus equity

About the Company

Our partner is an early-stage, venture-backed AI infrastructure startup that has raised more than $10M from well-known investors. They run a hardware-agnostic inference platform for open-source models, operating across several kinds of silicon and using intelligent routing and optimization to deliver inference at a meaningfully lower cost than the market. The team is small and senior, and their ambition is to become the default platform for GPU and high-performance compute.

The Opportunity

This is the second engineering hire and the owner of the platform. You will be responsible for the entire platform engineering vertical, including the user interface, backend services, customer onboarding, fraud detection, virtual machine onboarding and Kubernetes. The core inference engine is owned separately, so your focus is everything that makes the platform usable, reliable and scalable for customers.

Their team operates on trust and ownership. You and the technical co-founder agree on outcomes and constraints, and the implementation decisions are yours to make. It is a demanding, early-stage environment that suits engineers who want real autonomy, meaningful equity and the chance to shape a platform from its foundations.

Responsibilities

• Own the platform engineering vertical end to end, from UI to infrastructure
• Build and operate backend services and Kubernetes-based platform infrastructure
• Design customer onboarding, virtual machine onboarding and fraud detection systems
• Make architecture, tooling and vendor decisions independently within agreed constraints
• Deliver against high-level goals and communicate approach and outcomes to the team
• Operate costly compute infrastructure responsibly and confidently

Requirements

• 3-5 years of software engineering experience
• Full-stack capability across UI, backend and Kubernetes or platform infrastructure
• Prior startup experience and a track record of owning a system end to end
• Demonstrated ability to make significant technical decisions autonomously
• Experience with GPU infrastructure, bare-metal orchestration or high-performance computing is strongly preferred
• Willingness to work the demanding hours of an early-stage company