Snowflake
Software Engineer AI Team
- Jenis pekerjaan
- Penuh waktu
- Cara kerja
- Hibrida
- Lokasi
- PL-Warsaw-Lixa C
- Dipublikasikan
- 1 Okt 2026
- Terakhir diperiksa
- 26 Okt 2026
Tentang posisi ini
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
We’re at the forefront of the data revolution, committed to building the world’s greatest data and applications platform. Our ‘get it done’ culture allows everyone at Snowflake to have an equal opportunity to innovate on new ideas, create work with a lasting impact, and excel in a culture of collaboration.
We're looking for a talented and motivated Software Engineer to join the Cortex AI Functions https://docs.snowflake.com/en/user-guide/snowflake-cortex/aisql Platform team. AI functions are how Snowflake customers call AI directly from SQL, running models over their own tables without moving data out of the platform. Our team builds the platform that makes this work at data warehouse scale, where a single statement can expand into a large volume of inference requests that must complete predictably, within expected cost, and without compromising the query when a dependency degrades or fails.
Current projects include a new architecture for multi-modal inference, quality gates that let us ship new functions and models with confidence at batch scale, and support for input data beyond plain text. Alongside these, we work continuously on throughput, cost and reliability as customer usage grows, and on making failures in the inference path easier to detect, diagnose and recover from.