Senior AI Engineer, Enterprise

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.

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.

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.