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 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.
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.
Stay current with advances in AI engineering and help drive adoption of modern technologies, frameworks, and development practices across the team.
5+ years of professional software engineering experience with a Bachelor's degree (or higher) in Computer Science, Software Engineering, or a related technical field.
Strong proficiency in Python (3.11+) with experience writing production-quality, well-tested, maintainable code using modern Python practices.
Experience building RESTful APIs and backend services using FastAPI or similar frameworks.
Experience designing and operating distributed systems and microservice architectures.
Strong understanding of software engineering best practices, including testing, CI/CD, code quality, observability, and production operations.
Experience with containerization technologies such as Docker.
Hands-on experience building production AI applications using large language models.
Experience with prompt engineering, tool calling, structured outputs, and LLM orchestration frameworks.
Strong problem-solving skills, excellent communication, and the ability to work effectively in a fast-paced, collaborative environment.
Experience with the Snowflake platform, including Snowpark, Cortex AI, Snowpark Container Services, Snowflake Connector, and Snowflake CLI.
Experience building agentic applications using frameworks such as LangGraph or similar multi-agent orchestration frameworks.
Experience with AI evaluation, monitoring, guardrails, and observability frameworks.
Familiarity with model serving, inference optimization, and AI infrastructure.
Experience working with large-scale data platforms, ETL pipelines, and modern data engineering workflows.
Experience building full-stack AI applications using Streamlit, React, or similar frameworks.
Experience with Python data libraries such as pandas and NumPy.
Familiarity with modern AI development tools such as Cursor, Claude Code, Cortex Code, or similar AI-assisted development environments.
Experience working with cloud-native infrastructure and Kubernetes is a plus.
Joining the GTM AI Engineering team means building AI products that have a direct and measurable impact on Snowflake's business. You'll help define the architecture of our internal AI platform while developing intelligent applications used every day by thousands of employees across our global Go-To-Market organization.
This is a unique opportunity to combine backend engineering, distributed systems, and applied AI to solve real business problems at scale. You'll work alongside world-class engineers and product leaders while helping shape how AI transforms the way Snowflake operates internally.
If you're passionate about building production-grade AI systems, enjoy solving complex engineering challenges, and want to help define the future of enterprise AI, we'd love to hear from you.
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