Responsibilities
- Architect, build, and deploy enterprise-grade AI solutions and AI agents from prototype to production.
- Design and ship scalable AI applications and ML pipelines using Python and SQL.
- Own the implementation lifecycle, including deployment, monitoring, optimization, data validation, and observability.
- Partner with customer data science and engineering teams as a technical advisor.
- Collaborate with Snowflake Product and Engineering teams and share customer feedback to influence the AI platform.
Requirements
- Bachelor’s degree in Computer Science, Engineering, 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 the MLOps lifecycle, including model deployment, monitoring, and evaluation in AWS, Azure, or GCP.
- Preferred understanding of data warehousing principles, architecture, and best practices.
- Customer-facing technical experience, such as solutions architecture, and startup experience are preferred.
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.