Sr. Technical Architect - AI/ML
Summary
Senior Technical Architect designing and supporting enterprise AI/ML deployments on the Snowflake native stack, performing root cause analysis across distributed cloud systems, and mentoring teams on MLOps best practices.
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
LEAD. STRATEGIZE. TRANSFORM.
We are seeking an advanced professional handling complex enterprise AI/ML deployments, deconstructing system dependencies, and ensuring production robustness.
WHY THIS ROLE?
This role marks a shift from managing tactical tasks to managing strategic outcomes. You are a seasoned professional with a full understanding of your specialization, resolving a wide range of issues in creative ways.
WHAT YOU'LL DO:
Design robust, scalable AI/ML solutions utilizing the full Snowflake native stack and partner ecosystem.
Perform deep-dive Root Cause Analysis (RCA) for complex system dependencies in AI/ML solutions.
Collaborate cross-functionally with Sales and Product teams to align technical roadmaps with customer ROI.
Mentor Level 3 architects on best practices for MLOps and architectural design.
TECHNICAL DEPTH & RISK MANAGEMENT:
Distributed Systems: Deconstruct failures in complex pipelines involving external cloud services (AWS/Azure/GCP).
Predictive Failure Analysis: Critically think about potential failure modes like model drift and data skew early in the lifecycle.
Governance: Architect data security and access controls specifically for sensitive AI/ML training data.
SNOWFLAKE-NATIVE TECH STACK:
Snowflake Model Registry, Cortex Functions, Python, External MLOps (Kubeflow/SageMaker).
OUR IDEAL CANDIDATE WILL HAVE:
Typically requires a minimum of 8 years of related experience with a Bachelor's degree (Radford L4 equivalent).
Seasoned professional expertise in resolving wide-ranging issues in creative ways.
Strong executive communication: Ability to present complex AI/ML concepts and ROI to technical and business audiences.
Reduction in post-deployment technical debt; Regional success of complex implementations; Peer mentorship impact.
Thorough understanding of the complete Data Science life-cycle including feature engineering, model development, model deployment and model management.
BONUS POINTS FOR HAVING :
Experience with GenerativeAI, LLMs and Vector Databases.
Experience with Databricks/Apache Spark.
Experience implementing data pipelines using ETL tools.
Experience working in a Data Science role.
Proven success at enterprise software.
Vertical expertise in a core vertical such as FSI, Retail, Manufacturing, etc.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information:
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