AI Architect

The role

The Enterprise AI & Data Architect will define and lead the future-state architecture for data, analytics, AI, and cloud platforms. This role involves creating architectural blueprints, establishing standards, and guiding engineering teams to deliver scalable AI-native solutions.

What you will do

• Support the enterprise AI architecture roadmap.
• Develop reference architectures for Generative AI, Agentic AI, Predictive AI, and AI-powered analytics.
• Establish standards and design patterns for Cortex AI, Cortex Agents, Cortex Search, and Cortex Analyst.
• Define architecture principles for AI platforms, reusable AI services, and enterprise AI products.
• Evaluate emerging AI technologies.
• Define architecture standards for the Enterprise Data Warehouse and strategic data products.
• Design scalable, AI-ready data architectures.
• Establish patterns for batch, streaming, CDC, event-driven, and real-time data integration.
• Define cloud architecture patterns supporting Snowflake, AI workloads, data pipelines, and analytics services.
• Establish enterprise AI governance frameworks.

Required qualifications

• 8+ years of experience in Enterprise Architecture, Data Architecture, AI Architecture, Cloud Architecture, or related disciplines.
• Strong experience designing large-scale enterprise data platforms and modern cloud architectures.
• Deep understanding of Data Engineering, Analytics, Artificial Intelligence, and Machine Learning ecosystems.
• Strong knowledge of SQL and Python.
• Experience designing scalable, secure, and resilient enterprise systems.
• Experience defining architecture standards, governance processes, and technology roadmaps.
• Strong stakeholder management and communication skills.
• Proven experience leading cross-functional technology initiatives.

Nice to have

• Deep experience with Snowflake and associated platform services.
• Experience with Cortex AI, Cortex Agents, Cortex Search, Cortex Analyst, and Snowpark.
• Experience with Neo4J/native graph databases.
• Experience building AI-ready enterprise data platforms.
• Knowledge of Generative AI architectures, including Retrieval-Augmented Generation (RAG), Agentic AI, vector search, semantic layers, evaluation frameworks, and LLMOps.
• Experience with AWS cloud architecture and platform engineering.
• Experience implementing Infrastructure as Code and automated deployment frameworks.
• Strong understanding of Data Governance, Data Quality, Metadata Management, and Information Security.
• Fintech, Payments, Banking, or B2B SaaS experience.
• Snowflake certification(s).

About the company

Bottomline is a global leader in business payments and cash management with over 35 years of experience. The company moves more than $16 trillion in payments annually.