5 months ago
Base Salary
$160k - $230k/yr
Responsibilities
- Own Snowflake Database Engineering features end to end.
- Build agentic workflows, coding harnesses, and evaluation pipelines.
- Develop enterprise-grade context engineering with function calling, tool schemas, guardrails, agent teams, and verification and repair.
- Design evaluation golden sets, rubrics, metrics, error analyses, and experiments to improve results.
- Partner with product and infrastructure teams to translate customer problems into products and experiments and productionize improvements.
- Drive AI engineering from design and prompt/tool engineering through deployment, measurement, optimization, and production reliability.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Statistics, or a related field; a master’s or higher degree is preferred but not required.
- At least five years of experience shipping AI features in production.
- Proficiency in Python, TypeScript, or Go.
- Strong communication and collaboration skills.
- Experience with data engineering pipelines, data modeling, data analysis, retrieval systems, or semantic layers is a plus.
- Experience with agentic coding tools, model strengths and failure modes, eval harnesses, LLM observability, or production safety and guardrails is advantageous.
- Experience building and owning complex systems with pipelines, orchestration, substantial state, branching logic, and operational requirements is valuable.
Tech Stack
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.