Responsibilities
- Architect, build, iterate, and deploy enterprise-grade AI agents, pipelines, and production applications.
- Translate ambiguous customer objectives into scalable, performant solutions using Python and SQL.
- Own the full lifecycle of AI implementations, including prototyping, deployment, monitoring, and optimization.
- Partner directly with customer data science and engineering teams as a technical advisor.
- Implement data validation, SLA observability, and operational practices for reliable AI performance.
- Collaborate with Product and Engineering teams and share customer feedback to influence Snowflake’s AI platform.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- At least 3 years of professional software engineering experience.
- Hands-on experience building and shipping LLM-based or ML applications.
- Experience with data modeling, ETL/ELT development, performance tuning, and automated data workflows.
- Advanced proficiency in Python, Java, C++, or another backend programming language.
- Preferred experience building production LLM applications using RAG and agentic workflows.
- Preferred experience with model deployment, monitoring, and evaluation in a cloud environment such as AWS, Azure, or GCP.
- Strong understanding of data warehousing principles, architecture, and best practices.
- Customer-facing experience, such as work as a solutions architect, is preferred.
- Startup experience is preferred.
Benefits
- Opportunity to work with enterprise customers and Snowflake’s AI capabilities and infrastructure.
- Opportunity for progressive ownership and growth from components to workstreams and customer engagements.
- For U.S.-based roles, salary and benefits information is available on the Snowflake Careers Site.
About Snowflake
**Snowflake is proud to be the Official Data Collaboration Provider for LA28 and Team USA.** Snowflake delivers the AI Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the AI Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the AI Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the AI Data Cloud.