AI Engineer (Database Engineering)

Join Snowflake, a leading cloud data platform, as an AI Engineer specializing in Database Engineering. In this role, you will work on critical business initiatives, directly impacting how developers and businesses build with data. You will own the full AI engineering lifecycle, collaborate with a high-powered engineering team, and partner with product and infrastructure teams. Enjoy comprehensive health insurance, retirement plans, generous time-off, and more.

• Conception et mise en œuvre de solutions d'ingénierie AI pour le moteur de base de données.
• Responsabilité de l'ensemble du cycle de vie de l'ingénierie AI, y compris la conception, l'ingénierie des invites, les évaluations, le déploiement, la mesure et l'optimisation.
• Collaboration avec les équipes produit et infrastructure pour traduire les problèmes des clients en produits et expériences.
• Bachelor’s degree in Computer Science, Engineering, Statistics or a related field. Master’s or higher degree preferred but not a requirement
• You may be a particularly good fit if you:
• Prior work on eval harnesses, LLM observability, or safety / guardrails in production
• Proficiency in programming languages such as Python, Typescript, Go
• Take problems to completion independently: you don’t stop at a prototype; you care about production reliability and clear metrics
• Strong communication skills and ability to collaborate effectively in a team environment
• 5+ years of experience shipping AI features in production
• Background in data engineering (dbt, Airflow), data modeling, analytics, retrieval / RAG, or semantic layers — highly relevant for data-centric coding agents
• Have built and owned complex systems — pipelines, orchestration, or software with substantial state, branching logic, and operational requirements
• Are a power user of modern coding agents and care about turning that intuition into systematic measurement and improvement
• Thrive in high-intensity environments with short feedback loops and high standards for rigor
• Deep experience with agentic coding tools (e.g. IDE agents, CLI agents) and intuition for model strengths, failure modes, and prompting limits
• (Optional) Experience working with data engineering pipelines (dbt, airflow), data modeling, data analysis, retrieval systems, and semantic layers is a plus