Snowflake
Engineering
AIEngineer-DatabaseEngineering
Neural analysis suggests this role is
optimal for Senior candidates.
“AI Engineer - Database Engineering at Snowflake. Skills: AI engineering, Database Engineering, agentic workflows. Own features end-to-end. Build agentic workflows”
What You'll Achieve.
accelerate roadmap cycles; impact how developers and businesses build with data; production reliability; clear metrics; scaling our team; enable and accelerate our growth
Industry & Context.
solve problems; accelerate your impact; translate customer problems into products and experiments; Take problems to completion independently
What They're Looking For.
Must Have
5+ years of experience shipping AI features in production, Proficiency in programming languages such as Python, Typescript, Go, communication skills, ability to collaborate effectively in a team environment
Nice to Have
Master’s or higher degree, Experience working with data engineering pipelines (dbt, airflow), data modeling, data analysis, retrieval systems, semantic layers, Deep experience with agentic coding tools (e. g. IDE agents, CLI agents), intuition for model strengths, failure modes, and prompting limits, Background in data engineering (dbt, Airflow), data modeling, analytics, retrieval / RAG, semantic layers, Prior work on eval harnesses, LLM observability, safety / guardrails in production, built and owned complex systems — pipelines, orchestration, or software with substantial state, branching logic, and operational requirements, Thrive in high-intensity environments with short feedback loops and high standards for rigor, Take problems to completion independently, care about production reliability and clear metrics, power user of modern coding agents, care about turning that intuition into systematic measurement and improvement
What You'll Do.
Own features end-to-end
Build agentic workflows
Build coding harnesses
Build evaluation pipelines
Build enterprise-grade context engineering
Design evals and hillclimb
Partner with product and infra
translate customer problems into products
Collaborate with infrastructure teams
How You'll Work.
Team & Collaboration
Collaborate with product and infra; Collaborate with infrastructure teams; Work with an elite team of engineers; collaboration
Communication Scope
communication skills; ability to collaborate effectively
Full Job Description
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level. About the Role You will work on critical business initiatives in the core database engine, bring an AI-forward approach to software development and accelerate roadmap cycles for the benefit of our customers. Your work will directly impact how developers and businesses build with data. You'll own the full AI engineering lifecycle: design, prompt/tool engineering, evals, deployment, measurement, and optimization. You'll work with a small, high-powered engineering team. What you will do in this role: - Own features end-to-end for Snowflake Database Engineering products. Build agentic workflows, coding harnesses, evaluation pipelines. - Build enterprise-grade context engineering: function calling, tool schemas, guardrails, agent teams, and verification/repair. - Design evals and hillclimb : create golden sets, create rubrics and metrics, analyze errors, run experiments to hill climb on the metrics. - Partner with product and infra: translate customer problems into products and experiments. Collaborate wi
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