2 months ago
Base Salary
$264k - $380k/yr
Responsibilities
- Define the long-term technical vision and architecture for Snowflake Intelligence.
- Lead the design of multi-agent systems, complex tool-use frameworks, and self-correcting NL-to-SQL engines.
- Build automated hill-climbing infrastructure and methodologies for reliable LLM performance evaluation.
- Partner with product, engineering, and research leaders to bring LLM capabilities into production at Snowflake scale.
- Design extensible context-engineering patterns, advanced function calling, and semantic-layer integrations.
- Mentor Staff and Senior engineers and lead cross-functional strike teams on high-stakes projects.
Requirements
- 10+ years of software engineering experience, including 3+ years leading deployment of LLM-based applications at massive scale.
- Bachelor’s, Master’s, or PhD in Computer Science, AI, or a related field.
- Deep expertise in LLM orchestration, prompt optimization, semantic modeling, and guardrails for non-deterministic systems.
- Proven experience designing complex systems integrating AI with SQL, retrieval systems, and semantic layers.
- Exceptional ability to communicate technical trade-offs to executive leaders and individual contributors.
- Prior Principal-level or equivalent high-level individual contributor experience, or technical leadership of a major AI product used by millions.
Tech Stack
SnowflakeSQL
Categories
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.