Senior AI Engineer

Location: Menlo Park, California, United States

Salary: $156K–$224.2K per year

Company

Snowflake builds cloud data and AI products, including an internal AI platform and intelligent applications for its Go-To-Market organization.

What you will do

• Design and build scalable backend services, distributed systems, APIs, and orchestration services for production AI and agentic applications.
• Develop reusable AI platform components, including agent frameworks, evaluation pipelines, developer SDKs, templates, and shared Python libraries.
• Improve CI/CD pipelines, automated testing, deployment tooling, observability, monitoring, and developer experience.
• Optimize AI infrastructure and backend services for performance, scalability, reliability, security, and cost efficiency.
• Use Snowflake Cortex, Snowpark, and the broader Snowflake AI ecosystem to build intelligent data applications.
• Collaborate with product managers, data engineers, designers, and Go-To-Market stakeholders on high-impact AI solutions.

Requirements

• 5+ years of professional software engineering experience and a Bachelor’s degree or higher in Computer Science, Software Engineering, or a related field.
• Strong proficiency in Python 3.11+ and experience writing production-quality, well-tested, maintainable code.
• Experience with RESTful APIs, FastAPI or similar frameworks, distributed systems, microservices, and Docker.
• Strong knowledge of testing, CI/CD, code quality, observability, monitoring, and production operations.
• Hands-on experience building production AI applications with large language models, prompt engineering, tool calling, structured outputs, and LLM orchestration.
• Strong problem-solving, communication, and collaboration skills.

Nice to have

• Experience with Snowpark, Cortex AI, Snowpark Container Services, Snowflake Connector, or Snowflake CLI.
• Experience building agentic applications with LangGraph or similar multi-agent orchestration frameworks.
• Knowledge of AI evaluation, monitoring, guardrails, observability, model serving, inference optimization, and AI infrastructure.
• Experience with large-scale data platforms, ETL pipelines, Streamlit, React, pandas, NumPy, Kubernetes, or cloud-native infrastructure.
• Familiarity with AI-assisted development tools such as Cursor, Claude Code, or Cortex Code.

Culture & Benefits

• Work on production AI systems used daily by thousands of employees.
• Contribute to a rapidly growing internal AI platform with direct business impact.
• Collaborate with engineers, product leaders, and stakeholders across the global Go-To-Market organization.
• Help establish engineering best practices and adopt modern AI development technologies.