3 months ago
Warsaw, PolandMid Level
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 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.