ABOUT THE TEAMThe 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.
- Stay current with advances in AI engineering and help drive adoption of modern technologies, frameworks, and development practices across the team.
WE WOULD LOVE TO HEAR FROM YOU IF YOU HAVE:Required Qualifications- 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.
Preferred Qualifications- 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.
