Snowflake Logo

Snowflake

AI Engineer - Database Engineering

Reposted 2 Days Ago
In-Office
Menlo Park, CA, USA
160K-230K Annually
Senior level
In-Office
Menlo Park, CA, USA
160K-230K Annually
Senior level
In this role, you will lead the AI engineering lifecycle for Snowflake Database Engineering products, enhancing workflows and collaborating to address customer needs.
The summary above was generated by AI

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 with infrastructure teams to productionize improvements.

  • Work with an elite team of engineers towards building great products

REQUIREMENTS:
  • Bachelor’s degree in Computer Science, Engineering, Statistics or a related field. Master’s or higher degree preferred but not a requirement.

  • 5+ years of experience shipping AI features in production.

  • Proficiency in programming languages such as Python, Typescript, Go

  • Strong communication skills and ability to collaborate effectively in a team environment.

  • (Optional) Experience working with data engineering pipelines (dbt, airflow), data modeling, data analysis, retrieval systems, and semantic layers is a plus.

NICE TO HAVE:
  • Deep experience with agentic coding tools (e.g. IDE agents, CLI agents) and intuition for model strengths, failure modes, and prompting limits.

  • Background in data engineering (dbt, Airflow), data modeling, analytics, retrieval / RAG, or semantic layers — highly relevant for data-centric coding agents.

  • Prior work on eval harnesses, LLM observability, or safety / guardrails in production.

You may be a particularly good fit if you:

  • Have 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: you don’t stop at a prototype; you care about production reliability and clear metrics.

  • Are a power user of modern coding agents and care about turning that intuition into systematic measurement and improvement.


Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

Snowflake Dublin, California, USA Office

4140 Dublin Blvd., Dublin, CA, United States, 94568

Snowflake Menlo Park, California, USA Office

135 Constitution Dr, Menlo Park, CA, United States, 94025

Similar Jobs

4 Hours Ago
In-Office or Remote
Senior level
Senior level
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software • Business Intelligence • Data Privacy
The role involves designing cloud infrastructure, managing production Kubernetes clusters, optimizing CI/CD pipelines, enhancing developer experience, and ensuring reliable AI workloads. Candidates should have extensive experience in infrastructure and distributed systems engineering with strong coding skills and cloud expertise.
Top Skills: AWSAzureDatadogDockerElkGCPGoGrafanaJavaKubernetesPrometheusPythonTerraform
4 Hours Ago
Hybrid
San Jose, CA, USA
37K-66K Hourly
Senior level
37K-66K Hourly
Senior level
Fintech • Financial Services
Acquire and deepen relationships with affluent consumer and business customers, manage a book of business, deliver multi-product financial solutions (deposits, lending, investments), coordinate with Wealth/Home Lending/Business Banking partners, drive digital adoption, ensure accurate documentation and regulatory compliance, and meet licensing/SAFE registration requirements.
4 Hours Ago
Hybrid
23-31 Hourly
Entry level
23-31 Hourly
Entry level
Fintech • Financial Services
Frontline branch role building customer relationships, supporting account openings, service requests, credit applications, and cash-handling/teller activities. Drive branch growth through discovery conversations, referrals, and digital tool adoption while maintaining compliance, risk controls, and collaborating with branch teammates to deliver seamless customer service.

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account