Sr. Enterprise Data & AI Architect
Listed on 2026-06-27
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IT/Tech
AI Engineer (Applied/Software), Data Engineering, Cloud Computing: Infrastructure & Operations
Sr Enterprise Data & AI Architect
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.
Snowflake empowers enterprises and people to reach their full potential. Our culture is centered on impact, innovation, and collaboration, creating a place where you can build big, move fast, and grow your career.
We're looking for a Sr Enterprise Data & AI Architect to join a specialized team that guides our largest customers through complex data and AI transformations. Reporting to the Director of AFE Architecture, this person will:
- Shape enterprise data and AI architectures across AWS, Azure, GCP, and the Snowflake Data Cloud
- Provide hands-on technical leadership in Enterprise Data Platforms, Enabling a Data Driven Organizational Culture, AI/ML
- Advise C-level executives (e.g. CTO, CDO, VP Engineering) on strategic architecture decisions and investment choices.
This role blends deep hands on technical expertise with executive presence. You should be able to design sophisticated AI/ML solutions and comfortably influence technology strategy at Fortune 500 organizations.
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).
- 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.
- 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.
- 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.
- 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.
- 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.,…
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