Sr. Enterprise Data & AI Architect

Snowflake Snowflake · Data AI · CA-Menlo Park, United States · Solution Engineering

Snowflake is seeking a Sr. Enterprise Data & AI Architect to guide large customers through complex data and AI transformations. This role involves shaping enterprise data and AI architectures, providing technical leadership in AI/ML, and advising C-level executives on strategic decisions. The architect will design modern AI/ML solutions on Snowflake, including MLOps/LLMOps and RAG/agentic patterns, ensuring secure and governed deployments. The position requires deep hands-on technical expertise, executive presence, and a strong understanding of cloud data platforms and AI governance.

What you'd actually do

  1. Be part of a specialized team scaling thought leadership and driving direct complex, architecture‑level customer engagements (L400/L500) across the entire Snowflake sales organization
  2. Design and review modern AI/ML architectures on Snowflake, including data platforms, pipelines, and production applications.
  3. Define MLOps/LLMOps and RAG/agentic patterns for training, deployment, and monitoring at scale.
  4. Ensure secure, governed AI/ML deployments, including LLM safety, data privacy, and compliance.
  5. Act as a trusted advisor to senior technology and business executives on data and AI transformation.

Skills

Required

  • 15+ years in enterprise architecture, solutions engineering, or similar technical leadership roles
  • Deep hands-on AI/ML experience, including LLMs, ML pipelines, and AI application architectures
  • Expert-level knowledge of cloud data platforms (e.g., Snowflake, Databricks, AWS, Azure, GCP) and multi-cloud architectures
  • Proven track record influencing executive-level technology decisions at large enterprises
  • Strong understanding of AI governance, data privacy, and compliance for enterprise AI
  • Solid technical foundation: SQL mastery, Python/data engineering, and familiarity with the modern data stack
  • Expertise in modern AI architecture patterns (MLOps/LLMOps, RAG, vector databases, agentic frameworks)
  • Evidence of building AI business cases and TCO models, and demonstrating measurable ROI
  • Exceptional communication skills, with the ability to simplify complex concepts for executive audiences

Nice to have

  • Experience leading architecture practices at a major cloud provider or enterprise software company
  • Published thought leadership in data architecture, AI/ML, or cloud transformation
  • Direct experience architecting and operating production AI/ML systems at scale
  • Background in professional services, consulting, or customer-facing technical roles

What the JD emphasized

  • AI/ML
  • AI governance, data privacy, and compliance
  • AI business cases and TCO models
  • modern AI architecture patterns (MLOps/LLMOps, RAG, vector databases, agentic frameworks)

Other signals

  • AI-native thinkers
  • AI as a high-trust collaborator
  • reinvent how they work
  • complex data and AI transformations
  • modern AI/ML architectures
  • MLOps/LLMOps
  • RAG/agentic patterns
  • secure, governed AI/ML deployments
  • AI governance, data privacy, and compliance
  • AI business cases and TCO models