Sr. Technical Architect

Snowflake Snowflake · Data AI · Washington, DC · Remote · Professional Services

Senior Technical Architect role focused on leading customer engagements, architecting and implementing end-to-end AI/ML solutions on Snowflake, and driving adoption of Snowflake's AI product suite. The role involves defining MLOps practices, leading replatforming efforts, and influencing product direction.

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
  • AI/ML platforms
  • Snowflake production environments
  • Data modeling
  • Performance tuning
  • Security design
  • Platform governance
  • 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
  • MLOps frameworks
  • Model lifecycle management

Nice to have

  • Generative AI
  • Large language models (LLM)
  • Center of Excellence
  • Architectural standards
  • Services organization experience
  • Cloud certifications (AWS, GCP, Azure)
  • Snowflake certifications
  • Industry vertical expertise

What the JD emphasized

  • AI/ML solutions on Snowflake
  • MLOps practices
  • AI/ML lifecycle
  • 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