Senior Software Engineer - Capacity

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

SENIOR SOFTWARE ENGINEER, CAPACITY ENGINEERING

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic, fast-moving environments and approach challenges with an experimental mindset, rapidly testing emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

Snowflake’s infrastructure is expanding rapidly across AWS, Azure, and GCP. The Capacity team plays a pivotal role in provisioning the cloud resources essential for Snowflake's operations and ongoing growth. Capacity Engineering accurately models demand, forecasts requirements, and delivers optimal CPU and GPU capacity on schedule. We drive hardware cost-efficiency and price/performance while continually maximizing fleet utilization. To achieve this across all major cloud providers, the team is building a centralized, self-serve internal capacity platform. This software-driven system provides early visibility into supply risks, ensures sufficient lead time for capacity deployment, and maintains high utilization across committed cloud resources.

The technical problem spans the full lifecycle. We model demand and supply as first-class data, reconcile heterogeneous provider telemetry and commitments into a single canonical capacity layer, and make the live state of the fleet legible and actionable in real time. That includes CPU and GPU procurement and reservation lifecycle for AI/ML workloads (training, fine-tuning, and model serving), demand forecasting, cloud resource and cost optimization, hardware evolution analysis as new generations become available (price/performance, cross-family flexibility, migration paths), and the allocation and efficiency systems that close utilization gaps with the teams that own those workloads.