Staff Fullstack Engineer

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. The Cortex Apps team is building the future of AI for enterprise data. This role focuses on the backend infrastructure that powers our flagship products like Snowflake Intelligence, Cortex Agents and Search making agentic AI fast, reliable, scalable and secure at the enterprise level. You won’t just be using AI tools; you will be building the high-performance systems that orchestrate them. You’ll own and influence the architecture for agent execution environments, high-throughput context retrieval, or the ecosystem that allows our customers to iterate and launch agents in production. WHAT YOU WILL DO IN THIS ROLE: * Architect Agentic Runtimes: Build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management. * Scale Context Engineering Infra: Design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable and efficient search indexing, query processing, and result ranking, semantic caching, and automated metadata extraction. * Build the "Evals Engine": Develop the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and "hillclimbing" experiments. * Productionize AI Workflows: Collaborate with the modeling team to take raw LLM capabilities and turn them into hardened, multi-tenant microservices with strict guardrails and observability. * Optimize Performance & Cost: Direct the infra strategy for model routing, prompt caching, and token optimization to ensure Snowflake’s AI features are the most efficient in the industry. REQUIREMENTS: * Education: Bachelor’s degree in Computer Science or a related technical field. * Experience: 5+ years of experience building distributed systems, high-throughput APIs, or backend infrastructure for AI/ML products. * Technical Stack: Deep proficiency in Go or Java (for systems) and Python (for AI orchestration). * Systems Thinking: Strong understanding of database internals, distributed state management, and cloud-native architecture (Kubernetes, FoundationDB, etc.). * Domain Expertise: Familiarity with the "plumbing" of AI: vector indices, agent platforms, and building scalable data pipelines. (BONUS) EXPERIENCE WITH: * Query optimization and SQL engine internals. * Designing multi-tenant systems that handle sensitive enterprise data at scale. * Developing search infrastructure for large-scale applications. * Direct experience with any of the subsystems outlined above. 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

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