3 months ago
Warsaw, PolandMid Level
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 builds a cloud-native data platform used by enterprises to store, integrate, share, and analyze data across AWS, Azure, and Google Cloud. Its core products span data warehousing, data lakes, data engineering, and governed data sharing, sold via consumption-based subscriptions. Founded in 2012 and publicly traded on the NYSE (SNOW) following a 2020 IPO, Snowflake supports analytics and data application workloads across industries.