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.
Accountabilities
-
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.
Requirements
-
3โ5 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.
Benefits
-
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.