Sr. Technical Architect

Snowflake Snowflake · Data AI · New York, NY · 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. The role involves customer leadership, technical advisory, driving MLOps practices, and influencing product direction, with a strong emphasis on production AI/ML workloads and Snowflake's AI product suite.

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

  • 8+ years of experience in solutions architecture, technical consulting, data engineering, or a senior customer-facing technical role
  • Demonstrated track record leading architecture decisions on large-scale, enterprise data and AI platforms
  • Deep hands-on experience implementing Snowflake in production environments, including data modeling, performance tuning, security design, and platform governance
  • Expert-level understanding of the full data analytics stack, from ETL and data pipelines to data platform architecture, BI tooling, and semantic layers
  • Strong grasp of the AI/ML lifecycle, from data preparation and feature engineering through model training, deployment, monitoring, and ongoing governance
  • Proficiency in SQL and Python; ability to produce and review production-quality code as part of delivery leadership
  • Experience designing and implementing MLOps frameworks and model lifecycle management at enterprise scale
  • Proven ability to influence senior technical and executive stakeholders and navigate complex organizational dynamics

Nice to have

  • Hands-on experience with generative AI and large language model (LLM) use cases in production
  • Experience building and scaling a Center of Excellence or establishing architectural standards across a large enterprise
  • Background in the 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)
  • Experience as a technical lead on multi-team or multi-vendor delivery programs

What the JD emphasized

  • AI/ML solutions on Snowflake
  • MLOps practices
  • AI/ML workloads onto Snowflake
  • full data analytics stack
  • AI/ML lifecycle
  • MLOps frameworks
  • generative AI and large language model (LLM) use cases

Other signals

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