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San Francisco, California, United States
Remote only
This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Platform Engineer - OpenRelay based in the United States.
Take ownership of the platform engineering function at an ambitious, early-stage AI infrastructure startup building next-generation inference solutions for open-source models. As a key engineering hire, you will shape the systems and services that make the platform accessible, reliable, and scalable for customers. Your scope will span full-stack development, backend services, Kubernetes infrastructure, customer onboarding, and compute orchestration. Working closely with the technical co-founder, you will have significant autonomy over architecture, tooling, and implementation decisions. This opportunity is ideal for a hands-on engineer who thrives in fast-moving startup environments and wants to make foundational technical decisions. You will also have the opportunity to contribute to a high-impact AI infrastructure platform while participating in its long-term growth through equity.
Own the platform engineering function end to end, covering the user interface, backend services, and underlying infrastructure.
Build, deploy, and operate backend services and Kubernetes-based platform infrastructure to support reliable, scalable customer experiences.
Design and implement customer onboarding workflows, virtual machine provisioning and onboarding systems, and fraud detection capabilities.
Make independent decisions on system architecture, technology selection, tooling, and vendors within agreed business and technical constraints.
Translate high-level objectives into practical engineering plans, deliver results, and communicate technical approaches and outcomes clearly to the team.
Ensure the platform remains usable, reliable, and scalable as customer needs and infrastructure demands evolve.
Manage expensive compute resources responsibly, balancing performance, reliability, operational complexity, and cost.
Collaborate closely with technical leadership to establish priorities and build the platform from its foundations.
3–5 years of professional software engineering experience.
Full-stack engineering capabilities, including experience across user interfaces, backend systems, and Kubernetes or platform infrastructure.
Previous startup experience, with a demonstrated ability to take ownership of systems from design and implementation through deployment and ongoing operation.
Strong technical judgment and the confidence to make significant architectural and implementation decisions independently.
Experience building reliable services and infrastructure in environments where scalability, operational efficiency, and cost management are important.
Familiarity with GPU infrastructure, bare-metal orchestration, or high-performance computing is strongly preferred.
Ability to work effectively in a lean, early-stage environment where priorities can shift and engineers are expected to take broad responsibility.
Strong problem-solving, communication, and collaboration skills, with the ability to align technical decisions with broader business goals.
Willingness to commit to the demanding pace and working hours that can accompany an early-stage startup.
Competitive compensation: Base salary ranging from $180,000 to $250,000 per year.
Equity opportunity: Equity participation in an early-stage, venture-backed AI infrastructure company.
Remote work: Remote working arrangements, with San Francisco, California, preferred as a location.
Significant technical ownership: Lead the platform engineering function and shape key architecture and implementation decisions.
High autonomy: Work directly with technical leadership, with ownership over how engineering objectives are achieved.
Foundational impact: Help build and scale a platform designed to make AI inference more efficient and accessible.
Early-stage environment: Join a small, senior team where individual contributions can have a substantial impact on the product and its evolution.