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.

Staff Software Engineer - Container Platform (Menlo Park)

About the Role

We build the foundational container platform that runs Snowflake's production, AI/ML, and CI workloads across AWS, Azure, and GCP, including a rapidly growing AI/ML footprint. Hundreds of large Kubernetes clusters under management and growing. The work is to make that fleet reliable, automated, and invisible to the thousands of engineers building on top of it.

This is a staff-level role on a senior, high-performing platform team. You'll own hard problems end to end, drive technical direction across teams, and build the automation and platform abstractions that make operating at this scale sustainable. There is significant unsolved work ahead: improving the developer experience for thousands of internal engineers and continuing to scale the platform to meet Snowflake's growth.

What You'll Do

Own the design and delivery of large, complex platform initiatives spanning cluster lifecycle management, multi-cloud automation, and internal developer tooling.
Identify and drive cross-team technical improvements across the platform, from architecture through adoption.
Make and defend architectural trade-offs grounded in reliability, scalability, and operational reality.
Act as a technical anchor for the team, developing expertise in others, raising engineering standards, and being the person engineers turn to on hard problems.
Treat internal engineers as your primary customers and measure success by their velocity and the reliability of their experience on the platform.

What We're Looking For

Significant experience designing and operating large-scale distributed systems in production.
Experience owning Kubernetes or similar orchestration systems in production at scale: cluster lifecycle, upgrades, and fleet management across a large heterogeneous fleet.
Proficient in Go or a comparable systems language.
Experience operating across multiple clouds (AWS, Azure, GCP).

What Sets You Apart

You've built platforms where your work quietly enabled hundreds or thousands of engineers to ship faster and more reliably. You've made platform decisions with real blast radius: deprecating an API, rolling out a breaking change, or designing a self-service experience that teams actually want to use. That's the scale we're building toward, and we want someone who's been there.

Nice to Have

Experience with GPU infrastructure or AI/ML training workloads at scale.
Open source contributions to Kubernetes or related ecosystem projects.

Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee’s duty to keep customer information secure and confidential.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com