Sr. Technical Architect

Snowflake Snowflake · Data AI · WA, United States · Remote · Professional Services

Senior Technical Architect for Snowflake's Services Delivery team, focusing on architecting and implementing end-to-end AI/ML solutions on Snowflake for enterprise customers. This role involves customer leadership, technical advisory, defining platform strategy, and driving adoption of Snowflake's AI product suite, including MLOps practices and replatforming complex AI/ML workloads. The ideal candidate has deep experience with Snowflake, the AI/ML lifecycle, MLOps, and SQL/Python, with bonus points for generative AI and LLM use cases.

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
  • Large-scale, enterprise data and AI platforms
  • Snowflake production environments
  • Data modeling
  • Performance tuning
  • Security design
  • Platform governance
  • Full data analytics stack
  • ETL and 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
  • Influence senior technical and executive stakeholders
  • Navigate complex organizational dynamics

Nice to have

  • Generative AI
  • Large language model (LLM) use cases in production
  • Building and scaling a Center of Excellence
  • Establishing architectural standards across a large enterprise
  • Services organization of a technology product company
  • AWS, Google Cloud, or Microsoft Azure Advanced certification(s)
  • Snowflake SnowPro Advanced Certification(s)
  • Deep industry vertical expertise (e.g., Financial Services, Healthcare, Media and Entertainment)
  • Technical lead on multi-team or multi-vendor delivery programs

What the JD emphasized

  • AI/ML solutions on Snowflake
  • MLOps practices
  • Snowflake's AI product suite
  • 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 (Cortex, Streamlit, Intelligence)
  • Replatforming AI/ML workloads