Senior Technical Program Manager - ML/AI

About the role

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 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.

Responsibilities

• Own and drive complex, cross-team ML/AI programs end-to-end — from scoping and planning through execution and launch — across model infrastructure, inference pipelines, AI functions, Cortex AI services, and AI-powered application features
• Partner with ML Engineers, Research Scientists, Product Managers, and Engineering Leaders to define program roadmaps, surface dependencies, and build execution plans that account for the unique uncertainty and iteration cycles inherent to ML/AI development
• Coordinate cross-org launches for AI features that span ML infrastructure, application surfaces (Streamlit, Notebooks, Cortex Code), and core platform — ensuring all teams ship cohesively and on time
• Navigate the ambiguity of AI development — adapt program structures to handle model experimentation cycles, evaluation gates, accuracy/latency tradeoffs, and the non-linear nature of ML research-to-production timelines
• Establish program governance and reporting cadences — track milestones, risks, decisions, and engineering health with clarity and rigor, and proactively escalate to leadership when programs need intervention
• Drive cross-functional alignment between ML/AI engineering, product, design, infrastructure, security, and legal/compliance teams on AI feature launches, model deployment, and responsible AI practices
• Identify and resolve systemic execution bottlenecks — design lightweight processes and tooling-backed workflows that improve engineering velocity without adding overhead
• Own AI launch readiness — coordinate model evaluation sign-off, performance benchmarking, safety review, and documentation across engineering, product, and trust/safety teams
• Represent ML/AI programs to senior leadership with crisp, data-backed status updates and strategic recommendations that connect program execution to business outcomes