Sr. Enterprise Data & AI Architect

Key Responsibilities

Strategic Architecture Leadership

• Be part of a specialized team scaling thought leadership and driving direct complex, architecture-level customer engagements (L400/L500) across the entire Snowflake sales organization
• Define and drive cloud integration strategies across major cloud providers and key ecosystem partners
• Oversee and build proofs of concept, migrations, and modernization programs, providing hands-on technical guidance
• Create reusable assets (presentations, reference architectures, and implementation guides)

AI & Data Platform Architecture

• Design and review modern AI/ML architectures on Snowflake, including data platforms, pipelines, and production applications
• Guide customers in moving from legacy to cloud-native, AI-ready architectures
• Architect solutions leveraging Snowflake Cortex, ML capabilities, and integrations with leading AI frameworks
• Ensure secure, governed AI/ML deployments, including LLM safety, data privacy, and compliance
• Define MLOps/LLMOps and RAG/agentic patterns for training, deployment, and monitoring at scale
• Advise on build vs. buy decisions and cost models for training, inference, and managed AI services

Competitive & Market Insight

• Develop a deep understanding of competitive cloud data and AI platforms and how Snowflake differentiates
• Build competitive playbooks, battle cards, and guidance for field teams
• Partner with Product and Engineering to inform a roadmap based on customer and competitive insights

Executive Advisory & Engagement

• Act as a trusted advisor to senior technology and business executives on data and AI transformation
• Lead high-stakes customer reviews where architecture choices have major strategic and financial impact
• Represent Snowflake at industry events, executive briefings, and strategic forums
• Help customers shape AI investment strategies using ROI frameworks and TCO/business case analysis

Team Development & Operations

• Mentor, and develop a world-class enterprise architecture practice across the broader solution engineering organizations
• Drive knowledge sharing and continuous learning within the team and across Sales, Customer Success, and Product

What You Bring

• 15+ years in enterprise architecture, solutions engineering, or similar technical leadership roles, with increasing scope
• Deep hands-on AI/ML experience, including LLMs, ML pipelines, and AI application architectures
• Expert-level knowledge of cloud data platforms (e.g., Snowflake, Databricks, AWS, Azure, GCP) and multi-cloud architectures
• Proven track record influencing executive-level technology decisions at large enterprises
• Strong understanding of AI governance, data privacy, and compliance for enterprise AI
• Solid technical foundation: SQL mastery, Python/data engineering, and familiarity with the modern data stack
• Experience in competitive enterprise selling, including platform displacement or co-existence
• Expertise in modern AI architecture patterns (MLOps/LLMOps, RAG, vector databases, agentic frameworks)
• Evidence of building AI business cases and TCO models, and demonstrating measurable ROI
• Exceptional communication skills, with the ability to simplify complex concepts for executive audiences
• Bachelor’s degree in Computer Science, Engineering, or related field; advanced degree preferred

Preferred

• Experience leading architecture practices at a major cloud provider or enterprise software company
• Published thought leadership in data architecture, AI/ML, or cloud transformation
• Direct experience architecting and operating production AI/ML systems at scale
• Background in professional services, consulting, or customer-facing technical roles