Senior AI Engineer

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. ABOUT THE ROLE We are seeking a Senior AI Engineer to build AI-powered applications and workflows that accelerate Snowflake’s go-to-market teams. This role sits within Data, Analytics & AI and focuses on turning ambiguous business problems into production-ready AI applications that improve how Snowflake teams work every day. The right candidate combines strong applied AI instincts with practical software, data, and product judgment, and is excited to partner closely with business stakeholders to ship systems that are useful, reliable, and measurable. Within DAA, this role helps advance Snowflake’s internal AI transformation by building high-impact GTM applications and workflows, improving how teams use data and AI in practice, and helping shape scalable patterns for future solutions. This role will help Snowflake act as Customer Zero for AI-powered GTM workflows by applying modern LLM capabilities and Snowflake AI products to real internal use cases, learning from adoption in production, and translating those learnings into scalable patterns and actionable product feedback. WHAT YOU’LL DO - Design, build, and maintain AI applications, and workflow automation tools for GTM use cases across the full product lifecycle, from problem definition and prototyping through production deployment, iteration, and ongoing support - Independently scope and deliver medium-sized projects, and contribute meaningfully to larger cross-functional initiatives - Translate ambiguous business needs into practical technical plans, balancing speed, maintainability, quality, and long-term architecture - Partner closely with teams such as Sales, Marketing, Customer Support, Product, and Engineering to understand workflow pain points and deliver solutions that improve productivity, decision-making, and execution - Apply modern LLM capabilities and Snowflake AI products in production-oriented ways to solve real business problems, including knowledge-rich workflows, internal copilots, recommendation systems, and decision-support applications - Work across the data, application, and AI stack, including semantic layers, retrieval systems, orchestration patterns, evaluation, and application logic - Build AI systems grounded in trusted enterprise data and strong engineering practices, with attention to reliability, observability, testing, measurement, and maintainability - Own production quality for delivered solutions, including debugging, monitoring, issue triage, and continuous improvement based on user feedback and operational signals - Help Snowflake act as Customer Zero by turning internal usage insights, workflow learnings, and implementation challenges into actionable feedback for product and platform teams - Contribute to team quality through strong documentation, reusable patterns, automation, and thoughtful engineering standards - Act as a go-to engineer in at least one area, help diagnose issues beyond your immediate domain, and mentor more junior teammates - Communicate clearly with stakeholders on scope, tradeoffs, timelines, risks, and outcomes WHAT WE’RE LOOKING FOR - Hands-on experience building and shipping applied AI or LLM-based systems for real user workflows - Demonstrated ability to independently own and deliver production-grade AI applications or workflow automation solutions for a business function or product area - 5+ years of experience in applied AI, machine learning engineering, data applications, or related technical roles - Strong Python and SQL skills, plus comfort working with data-intensive applications and modern data platforms - Experience with prompt design, evaluation, observability, orchestration, and production hardening for AI systems - Experience building systems that combine AI capabilities with semantic layers, retrieval systems, or other knowledge-rich workflows - Good judgment in turning ambiguous business problems into scoped, iterative deliverables - Experience collaborating directly with business stakeholders and translating workflow pain points into product solutions - Strong communication skills and a bias toward shipping, learning, and iterating - A quality mindset around testing, measurement, reliability, maintainability, and respons