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Sail builds inference and agent hosting infrastructure for deploying AI agents at scale. As a Member of Technical Staff on the Clusters team, you will be an early engineer on a rapidly growing product line, responsible for building the systems and infrastructure that automatically provision and manage large fleets of compute across clouds.
You will own the design and implementation of reliable cluster management systems, implement scheduling algorithms to maximize GPU utilization, and design highly-available systems that route around hardware faults and maintain service quality on unreliable hardware. You'll implement comprehensive monitoring and alerting to ensure high availability and help define future directions for the Clusters product, including fully autonomous remediation, self-serve operations, and bare-metal provisioning.
The role combines systems engineering, infrastructure, and product thinking. You'll work on problems that directly impact Sail's ability to scale AI workloads efficiently and reliably.
The interview process includes conversations with the CTO and Clusters team engineers, followed by an in-person interview day at Sail's San Francisco office featuring a 3-4 hour design and implementation exercise simulating real daily work (AI assistance encouraged), concluding with a presentation of your approach and results.
Sail operates from a downtown San Francisco office with a strong focus on team quality of life: all meals provided, Studio Display monitors at every desk, and a commitment to tools and amenities that save time and energy.
Requirements:
- Deep understanding of Kubernetes and related technology
- Product-focused approach to platform work with commitment to building robust, scalable, and ergonomic solutions for users
- Bonus: experience with cluster virtualization technology such as k3s or vCluster
