Staff Software Engineer, Cortex AI Functions

About the role

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.

About the team

Our vision is to make raw multimodal data agent-ready and useful for analytics at enterprise scale. With Snowflake AI Functions, we enable pipelines that transform PDFs, images, audio, and video into high-quality information for downstream agents and applications, with the scalability and performance of a data platform.

We bring semantic operators into SQL—extraction, classification, filtering, joins, summarization, and aggregation—so customers can process and analyze structured and unstructured data together in a single hybrid query or pipeline through Snowflake’s SQL query surface. Our work connects AI quality with database systems through AI-aware query planning, adaptive model selection, and semantic query optimization. We seek deep expertise in either AI quality and applied modeling or database systems.

As a Staff Software Engineer you will

- Serve as tech lead for a group of 2–4 engineers, independently driving a large project end to end—from problem definition and architecture through implementation, launch, and production outcomes.

- For AI quality initiatives, define model strategies tailored to product needs, balancing accuracy, cost, and latency. Drive evaluation, error analysis, prompt optimization, and model adaptation, including fine-tuning and post-training where appropriate. Guide model-specific hosting and inference optimizations with infrastructure partners, validating their impact on quality and performance.

- For database systems initiatives, advance AI-aware query planning, compiler optimizations, distributed execution, scheduling, and safe result reuse within SQL and data pipelines.

- Connect quality objectives with execution decisions; diagnose bottlenecks and improve correctness, reliability, observability, and efficiency across the data processing workflow.

- Co-define the product surface and business strategy with PMs and leadership, translating customer needs into product capabilities, priorities, and success metrics. Align partner teams and manage dependencies through delivery.

- Break complex projects into milestones, delegate work, unblock and mentor engineers, and maintain technical quality through hands-on contributions and design and code reviews.

Our ideal candidate will have