Staff Software Engineer, Cortex AI Functions
Snowflake · US-WA-Bellevue
About this role
## About the Role At Snowflake, we’re powering the era of the agentic enterprise. We’re looking for AI-native thinkers who are energized by reinventing how work gets done—using AI as a high-trust collaborator, moving fast with an experimental mindset, and delivering measurable impact. ## 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—backed by the scalability and performance of a data platform. We bring semantic operators into SQL workflows (e.g., **extraction, classification, filtering, joins, summarization, and aggregation**) so customers can process structured and unstructured data together in a single hybrid query or pipeline. We connect AI quality with database systems through **AI-aware query planning, adaptive model selection, and semantic query optimization**. ## What You’ll Do (Staff Software Engineer) - **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. - Choose a focus area and lead initiatives: - **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/post-training where appropriate). Partner on hosting/inference optimizations and validate quality/performance impact. - **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; 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 capabilities, priorities, and success metrics. Align partner teams and manage dependencies. - Break complex projects into milestones, delegate work, unblock and mentor engineers, and maintain technical quality through hands-on contributions, design reviews, and code reviews. ## What We’re Looking For - Deep expertise in **either**: - **AI quality & applied modeling**, **or** - **Database systems** (Expertise in both is not required.) - **8+ years** of relevant experience in software engineering, applied machine learning, or database systems, including independently leading multi-engineer projects from definition through production. - Strong fundamentals in **algorithms, data structures, and software design**; fluency in **C++, Java, or Python**; strong debugging and testing skills. - An **empirical approach**: clear metrics, disciplined experiments, root-cause analysis, and sound tradeoffs between quality, cost, and latency. - Strong **product sense** and a track record of co-defining product direction with PMs and leadership. ### Relevant Depth (Choose Your Track) - **AI Quality**: modeling, evaluation methodology, statistical experimentation, data quality, error analysis, automated optimization. Fine-tuning/post-training experience is a plus. - **Database Systems**: query optimizers, compilers, execution engines, distributed data processing, performance a
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