Director, AI & Data Enterprise Architecture

Snowflake•Menlo Park, CA

About The Position

Snowflake is about empowering enterprises to achieve their full potential and people too. With a culture that's all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology and careers to the next level. Snowflake is seeking a Director of AI & Data Enterprise Architecture to lead a specialized team providing expert technical guidance for complex cloud integration and strategic scenarios. The ideal executive combines deep technical and hands-on AI development experience to help enterprises modernize data and AI infrastructure and navigate competitive landscapes. Reporting to the VP of Solutions Engineering, this leader will guide customers through transformational journeys across AWS, Azure, GCP, and Data Platform environments, delivering strategic architectural guidance to accelerate adoption and drive measurable business outcomes. The role intersects platform architecture, data intelligence, and AI solutions. This role requires a unique blend of executive leadership presence and technical depth, someone who can architect sophisticated AI/ML solutions while also influencing C-level technology decisions across Fortune 500 enterprises.

Requirements

15+ years of experience in enterprise architecture, solutions engineering, or technical leadership roles with progressive responsibility
5+ years of people management experience, including building and leading high-performing technical teams in high-growth environments
Deep hands-on experience with modern AI/ML development, including familiarity with LLMs, ML pipelines, and AI application architecture
Expert-level knowledge of cloud data platforms (Snowflake, Databricks, AWS, Azure, GCP) with ability to architect complex multi-cloud solutions
Proven track record of influencing executive-level technology decisions at Fortune 500 enterprises
Understanding of AI governance, data privacy, and compliance requirements for enterprise AI deployments
Strong technical foundation including SQL mastery, Python/data engineering skills, and experience with modern data stack technologies
Experience with competitive selling in complex enterprise deals involving platform displacement or co-existence strategies
Expertise in modern AI architecture patterns: MLOps/LLMOps pipelines, RAG systems, vector databases, and agentic frameworks
Track record of building AI business cases, TCO models, and demonstrating measurable ROI from AI investments
Exceptional communication skills with ability to translate complex technical concepts for executive audiences
Bachelor's degree in Computer Science, Engineering, or related technical field; advanced degree preferred

Nice To Haves

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

Responsibilities

Lead and scale a high-performing Enterprise Architect team providing expert technical guidance for L400/L500 platform and architecture-focused customer engagements
Define and execute strategic cloud integration planning across major Cloud Service Providers (AWS, Azure, GCP) and ecosystem platforms
Drive proof-of-concept execution and hands-on technical support for complex migration and modernization initiatives
Develop reusable technical assets including presentations, architecture diagrams, and reference implementations
Provide hands-on technical leadership in designing and implementing modern AI/ML architectures on Snowflake
Guide customers in migrating from legacy platforms to cloud-native, AI-ready data architectures.
Architect solutions leveraging Snowflake Cortex, ML capabilities, and integration with leading AI frameworks
Deliver technical guidance on building production-grade AI applications, data pipelines, and analytics platforms
Design secure AI/ML architectures with appropriate governance controls, including LLM safety guardrails and data privacy protections
Design end-to-end MLOps and LLMOps pipelines including model training, evaluation, deployment, and monitoring at enterprise scale
Architect RAG (Retrieval-Augmented Generation) systems, agentic workflows, and multi-model orchestration patterns
Evaluate AI & Platform build vs. buy decisions, including cost modeling for inference, fine-tuning, and managed AI services
Lead competitive technical analysis and develop strategic positioning for complex, multi-platform customer environments
Build deep expertise in competitive cloud data platforms and articulate Snowflake's differentiated value proposition
Create technical battle cards, competitive playbooks, and strategic guidance for field teams
Partner with Product and Engineering to inform roadmap priorities based on competitive landscape
Serve as a trusted technical advisor to customer executives navigating complex data and AI transformation initiatives
Lead high-stakes customer engagements where architectural decisions have significant strategic implications
Build and maintain relationships with key customer stakeholders and technology decision-makers
Represent Snowflake at industry events, executive briefings, and strategic customer forums
Guide customers through AI investment decisions with ROI frameworks, TCO analysis, and business case development
Build, mentor, and scale a world-class team of enterprise architects with expertise spanning cloud platforms, AI/ML, and competitive analysis
Establish scalable processes for team member engagement including request intake, prioritization, and account strategy alignment
Drive knowledge sharing and continuous learning across the architecture team
Partner with Sales, Customer Success, and Product teams to maximize customer outcomes