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TL;DR
Senior Software Engineer (AI): Building and refining AI-native coding agents integrated with Snowflake's data platform with an accent on agent quality, cost efficiency, and production reliability. Focus on designing eval harnesses, debugging complex failures, optimizing model usage, and driving measurable user value in large-scale data engineering workflows.
Location
Location: Menlo Park, California, United States
Salary
Salary: $200,000 – $270,000 per year
Company
Snowflake powers data platforms for thousands of enterprises worldwide, focusing on AI-native solutions and data engineering tools.
What you will do
- Design and refine AI coding agent behaviors from prototype to production for data engineering workflows.
- Own agent quality end to end by building evaluation harnesses, diagnosing failures, and running experiments to improve metrics.
- Optimize cost and latency through techniques like prompt caching and model routing.
- Debug production failures and increase system robustness with regression testing.
- Build data pipelines to feed task insights back into evaluations and modeling.
- Onboard frontier models and collaborate with product and infrastructure teams to define success metrics.
Requirements
- Location: Must be based in the United States
- Bachelor’s degree in Computer Science, Engineering, Statistics, or related field; Master’s preferred.
- 6+ years of experience shipping software in production, including AI/LLM features.
- Fluency in Python, TypeScript, or Go with willingness to work across all three.
- Strong systems-thinking and measurement-first approach to optimize user outcomes.
- Excellent debugging and communication skills to collaborate across teams.
Nice to have
- Experience with agentic coding tools, eval harnesses, LLM observability, or safety in production.
- Background in data engineering, data modeling, analytics, retrieval/RAG, or semantic layers.
- Experience with large-scale datasets or production system logs.
Culture & Benefits
- Work in a fast-growing, innovative environment focused on AI and data engineering.
- Collaborate with a high-powered team impacting global enterprises.
- Emphasis on experimentation, rigor, and measurable impact.
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