SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Snowflake is seeking a Senior Technical Architect to join its Services Delivery organization. You will lead complex, high-priority customer engagements as the primary technical authority, owning architecture decisions and driving measurable outcomes across multi-workstream implementations. You'll partner with customer executives and senior technical leadership to define platform strategy, develop long-term roadmaps, and align Snowflake capabilities to business objectives.
Key responsibilities include architecting and implementing end-to-end AI/ML solutions on Snowflake, setting standards for scalability, performance, security, and operability. You'll define and champion MLOps practices within customer organizations, covering model deployment pipelines, monitoring, governance frameworks, and lifecycle management. You'll drive adoption of Snowflake's AI product suite (Cortex, Streamlit in Snowflake, Snowflake Intelligence) through architecture leadership and hands-on delivery.
You'll lead replatforming efforts for complex AI/ML workloads onto Snowflake, coordinating across customer engineering, data science, and platform teams. You'll serve as a bridge between Services Delivery, Go-to-Market, and Snowflake product teams, channeling customer feedback to influence product direction. You'll mentor junior architects and consultants, and contribute to developing reusable architecture patterns and reference implementations.
Required qualifications: BA/BS in computer science, engineering, mathematics, or equivalent practical experience. 8+ years in solutions architecture, technical consulting, data engineering, or senior customer-facing technical roles. Demonstrated track record leading architecture decisions on large-scale enterprise data and AI platforms. Deep hands-on experience implementing Snowflake in production, including data modeling, performance tuning, security design, and platform governance. Expert-level understanding of the full data analytics stack. Strong grasp of the AI/ML lifecycle. Proficiency in SQL and Python. Experience designing and implementing MLOps frameworks at enterprise scale. Proven ability to influence senior stakeholders and navigate complex organizational dynamics.
Bonus qualifications include hands-on generative AI and LLM production experience, Center of Excellence building experience, background in technology product company services, cloud certifications, Snowflake SnowPro Advanced Certification, and deep industry vertical expertise.
