
Senior Technical Architect
Posted Aug 8

Posted Aug 8
This is a fully remote position, open to applicants in New York.
• Take the lead on customer interactions as the main technical authority, responsible for architectural decisions and measurable outcomes in complex implementations.
• Collaborate with customer executives and senior technical leaders to establish platform strategies and long-term roadmaps.
• Convert vague business challenges into scalable technical solutions, complete with delivery paths and risk mitigation strategies.
• Act as the technical escalation point, facilitating the unblocking of delivery teams and resolving architectural challenges.
• Design and implement comprehensive AI/ML solutions using Snowflake.
• Define and advocate for enterprise MLOps practices, which encompass deployment pipelines, monitoring, governance, and lifecycle management.
• Promote the adoption of Snowflake’s AI product offerings, including Cortex, Streamlit in Snowflake, and Snowflake Intelligence.
• Oversee the replatforming of intricate AI/ML workloads to Snowflake.
• Connect Services Delivery, Go-to-Market, and Snowflake product teams by relaying customer feedback to shape product direction.
• Guide junior architects and consultants through mentorship.
• Create reusable architecture patterns, reference implementations, and delivery accelerators.
• BA/BS in computer science, engineering, mathematics, or a related field, or equivalent practical experience.
• Over 8 years of experience in solutions architecture, technical consulting, data engineering, or a senior customer-facing technical role.
• Proven track record of making architecture decisions for large-scale enterprise data and AI platforms.
• Hands-on experience with Snowflake in a production environment, including data modeling, performance tuning, security design, and platform governance.
• Deep understanding of the data analytics stack, which includes ETL, data pipelines, data platform architecture, BI tools, and semantic layers.
• Familiarity with the AI/ML lifecycle, covering data preparation, feature engineering, model training, deployment, monitoring, and governance.
• Proficient in SQL and Python, including the ability to produce and review production-quality code.
• Experience in designing and implementing enterprise-scale MLOps frameworks and managing model lifecycles.
• Capability to influence senior technical and executive stakeholders while navigating complex organizational dynamics.
• Experience with generative AI and LLM production, advanced cloud certifications, Snowflake SnowPro Advanced Certification, industry expertise, and multi-team or multi-vendor delivery experience are considered additional qualifications.
• Salary and benefits information is available on the Snowflake Careers Site for positions located in the United States.
• Equal employment opportunity protections are provided.
• Voluntary self-identification and confidential handling of demographic, veteran, and disability information are assured.
Autonomic Mind
alt.bank
ComboCurve
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