Applied AI Engineer

Snowflake is building a high-impact team to help the world’s most innovative companies unlock the power of AI. The role is within the Cortex AI team, focusing on building production-grade AI systems using Snowflake AI Platform, Cortex, and native LLM capabilities.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.
• 3+ years of professional software engineering experience.
• Passion for tackling complex and ambiguous technical challenges using cutting-edge research and AI.
• Experience building, evaluating, and tuning applications and pipelines involving machine learning models or data-intensive systems; familiarity with pandas, numpy, Snowpark.
• Proven hands-on experience with data modeling, ETL/ELT development, and performance tuning.
• Advanced proficiency in Python, with experience scripting and automating data workflows.
• Excellent problem-solving and communication skills.
• Ability to thrive in a fast-paced, dynamic environment and adapt quickly to Generative AI.

Preferred Qualifications:

• Experience building and productionizing applications using LLMs, including RAG and agentic workflows.
• Hands-on experience with the MLOps lifecycle in cloud environments (AWS, Azure, or GCP).
• Strong understanding of data warehousing principles, architecture, and best practices.
• Experience in a customer-facing role (e.g., solutions architect).
• Startup experience.

• Architect, build, and deploy enterprise-grade AI solutions, including sophisticated AI agents, owning the end-to-end lifecycle from prototype to production.
• Rapidly design, iterate, and ship high-quality code and ML pipelines using Python and SQL.
• Own the full lifecycle of AI solution implementation, including developing prototypes, deploying, monitoring, and optimizing in secure, large-scale production environments.
• Partner directly with customer data science and engineering teams as a technical expert and trusted advisor.
• Architect and implement rigorous data validation, maintain strict SLA observability, and manage complex system interdependencies.
• Collaborate cross-functionally with Snowflake’s Product and Engineering teams to share customer feedback and influence the AI platform's future.