AI 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.

ABOUT THE TEAM

The GTM AI Engineering team is part of Snowflake's Data Analytics & AI organization and builds the internal AI platform and intelligent applications that power Snowflake's Go-To-Market organization. We develop production-grade AI systems used daily by thousands of employees across Sales, Solution Engineering and Marketing.

As a Senior AI Engineer, you will build the backend services, platform infrastructure, and AI capabilities that power next-generation agentic applications. You will work at the intersection of distributed systems, backend engineering, applied AI, and internal product development, designing scalable, reliable, and secure systems that enable intelligent experiences with direct business impact.

This role offers the opportunity to shape a rapidly growing internal AI platform, establish engineering best practices, and build AI products that directly accelerate Snowflake's growth.

IN THIS ROLE, YOU WILL:

• Design and build scalable backend services and distributed systems that power production AI and agentic applications.

• Develop APIs, orchestration services, and platform capabilities for internal AI products.

• Build reusable AI platform components, including agent frameworks, evaluation pipelines, developer SDKs, templates, and shared Python libraries.

• Evolve our engineering platform through modern CI/CD pipelines, automated testing, deployment tooling, and developer experience improvements.

• Optimize AI infrastructure and backend services for performance, scalability, reliability, security, and cost efficiency.

• Leverage Snowflake Cortex, Snowpark, and the broader Snowflake AI ecosystem to build intelligent data applications.

• Establish engineering best practices around testing, observability, monitoring, evaluation, and production readiness for AI systems.

• Collaborate closely with product managers, data engineers, designers, and GTM stakeholders to deliver high-impact AI solutions.