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Salary: USD 166,000 - 249,000 / annual
Snowflake is seeking a Senior Technical Program Manager to own and drive complex, cross-team ML/AI programs end-to-end. You will scope, plan, execute, and launch initiatives spanning model infrastructure, inference pipelines, AI functions, Cortex AI services, and AI-powered application features.
Key responsibilities include:
- Own complex ML/AI programs from conception through launch, coordinating across ML Engineers, Research Scientists, Product Managers, and Engineering Leaders
- Define program roadmaps, surface dependencies, and build execution plans that account for the unique uncertainty and iteration cycles of ML/AI development
- Coordinate cross-org launches for AI features spanning ML infrastructure, application surfaces (Streamlit, Notebooks, Cortex Code), and core platform
- Navigate the inherent ambiguity of AI development by adapting program structures to handle model experimentation, evaluation gates, accuracy/latency tradeoffs, and non-linear research-to-production timelines
- Establish program governance and reporting cadences; track milestones, risks, decisions, and engineering health with rigor
- Drive cross-functional alignment between ML/AI engineering, product, design, infrastructure, security, and legal/compliance teams
- Identify and resolve systemic execution bottlenecks through lightweight processes and tooling-backed workflows
- Own AI launch readiness by coordinating model evaluation sign-off, performance benchmarking, safety review, and documentation
- Represent ML/AI programs to senior leadership with data-backed status updates and strategic recommendations
Snowflake is positioning itself as a leader in the agentic enterprise era, seeking AI-native thinkers who treat AI as a high-trust collaborator and thrive in dynamic, fast-moving environments with an experimental mindset.
REQUIREMENTS:
- 5+ years of technical program management experience at a cloud or AI-native technology company, with a track record of owning cross-team programs end-to-end
- Demonstrated experience managing ML/AI programs; understanding of the ML development lifecycle (training, evaluation, deployment, monitoring) and ability to manage programs around its unique iteration patterns and uncertainty
- Strong technical depth to engage meaningfully with ML engineers and research scientists on model architecture, inference infrastructure, evaluation metrics, and deployment tradeoffs
- Proven ability to operate in ambiguity; experience structuring execution around experimentation cycles and adapting plans as signals emerge
- Experience managing programs spanning 4+ engineering teams with competing roadmaps and shared dependencies
- Excellent communication skills; ability to synthesize complex technical and research concepts into clear, actionable narratives for leadership, product, and cross-functional audiences
- Strong program management fundamentals: dependency management, risk frameworks, milestone governance, stakeholder alignment, and escalation discipline
PREFERRED:
- Experience with LLM inference, fine-tuning, RAG architectures, or AI function platforms at production scale
- Background in model serving infrastructure, GPU/accelerator resource management, or ML platform engineering
- Familiarity with responsible AI practices—model evaluation, bias detection, safety review, and compliance workflows
- Experience with Snowflake's architecture or data cloud ecosystem
- Working knowledge of ML observability—monitoring model performance, drift detection, and production quality metrics
- Background launching customer-facing AI features where accuracy, latency, and cost are critical tradeoffs
