Sr. Technical Architect

Snowflake Snowflake · Data AI · CA-Menlo Park, United States · Professional Services

Senior Technical Architect role focused on leading customer engagements for AI/ML solutions on Snowflake, defining MLOps practices, driving adoption of Snowflake's AI products, and replatforming AI/ML workloads. The role involves customer leadership, technical architecture, delivery, and cross-functional influence.

What you'd actually do

  1. Lead customer engagements as the primary technical authority, owning architecture decisions and driving measurable outcomes across complex, multi-workstream implementations
  2. Architect and implement end-to-end AI/ML solutions on Snowflake, setting standards for scalability, performance, security, and operability across the customer's environment
  3. Define and champion MLOps practices within customer organizations, covering model deployment pipelines, monitoring, governance frameworks, and lifecycle management
  4. Drive adoption of Snowflake's AI product suite (Cortex, Streamlit in Snowflake, Snowflake Intelligence) through architecture leadership and hands-on delivery
  5. Lead replatforming efforts for complex AI/ML workloads onto Snowflake, coordinating across customer engineering, data science, and platform teams

Skills

Required

  • Solutions architecture
  • Technical consulting
  • Data engineering
  • Customer-facing technical role
  • Snowflake production environments
  • Data modeling
  • Performance tuning
  • Security design
  • Platform governance
  • Full data analytics stack
  • ETL
  • Data pipelines
  • Data platform architecture
  • BI tooling
  • Semantic layers
  • AI/ML lifecycle
  • Data preparation
  • Feature engineering
  • Model training
  • Model deployment
  • Model monitoring
  • Model governance
  • SQL
  • Python
  • Production-quality code
  • MLOps frameworks
  • Model lifecycle management

Nice to have

  • Generative AI
  • Large language model (LLM) use cases in production
  • Building and scaling a Center of Excellence
  • Establishing architectural standards
  • Services organization of a technology product company
  • AWS Advanced certification
  • Google Cloud Advanced certification
  • Microsoft Azure Advanced certification
  • Snowflake SnowPro Advanced Certification

What the JD emphasized

  • AI/ML solutions on Snowflake
  • MLOps practices
  • Snowflake's AI product suite
  • replatforming AI/ML workloads
  • full data analytics stack
  • AI/ML lifecycle
  • MLOps frameworks
  • generative AI and large language model (LLM) use cases in production

Other signals

  • AI/ML solutions on Snowflake
  • MLOps practices
  • Snowflake's AI product suite
  • replatforming AI/ML workloads