AI Architect
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Skills
About the role
Why Choose Bottomline?
Are you ready to transform the way businesses pay and get paid? Bottomline is a global leader in business payments and cash management, with over 35 years of experience and moving more than $16 trillion in payments annually. We're looking for passionate individuals to join our team and help drive impactful results for our customers. If you're dedicated to delighting customers and promoting growth and innovation - we want you on our team!
JOB DESCRIPTION
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Location |
India |
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Reports To |
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Level |
Individual Contributor / Architect (8+ years experience) |
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Team |
Enterprise Data Services (EDS) |
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Contract |
Permanent, Full-Time |
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Line Relationship |
Data Architect |
About the Team
Enterprise Data Services (EDS) is responsible for Bottomline's Enterprise Data Warehouse, Enterprise Analytics, Artificial Intelligence, Data Governance, and strategic data platforms.
Our mission is to transform business operations, products, and decision-making through trusted data and AI-powered capabilities. Our technology strategy is centred around Snowflake and its native AI ecosystem, including Cortex AI, Cortex Agents, Cortex Search, Cortex Analyst, Snowpark, and enterprise data products such as Customer Cube.
We operate at the intersection of Data Engineering, AI Engineering, Analytics, Governance, and Platform Engineering, building the foundations that enable the organisation to become truly AI-first.
The Role
We are seeking an experienced Enterprise AI & Data Architect to define and lead the future-state architecture for Bottomline's Data, Analytics, AI, and Cloud Platforms.
This role combines AI Architecture, Enterprise Data Architecture, Data Engineering Architecture, and Cloud Platform Architecture to ensure the organisation can scale trusted data products, AI-native solutions, and business-critical analytics on a secure, governed, resilient, and cost-effective foundation.
The Enterprise AI & Data Architect will report directly to the Senior Director of AI & Data Services and work closely with the existing Data Architect through a dotted-line relationship. Together, these roles will define and govern the enterprise architecture strategy for data, analytics, AI, integration, and cloud platforms.
While the Data Architect focuses on information architecture, data modelling, governance, and enterprise data standards, the Enterprise AI & Data Architect will focus on AI architecture, platform architecture, data engineering standards, cloud infrastructure, and the technical enablement of enterprise-scale AI solutions.
This role is both strategic and hands-on, requiring the ability to define long-term architecture roadmaps whilst also guiding engineering teams through the delivery of complex initiatives.
What You Will Do
Enterprise AI Strategy & Architecture
- 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 and determine their applicability to Bottomline.
- Create architectural blueprints that enable scalable and governed AI adoption across the organisation.
Data Platform & Data Engineering Architecture
- Define architecture standards for the Enterprise Data Warehouse and strategic data products.
- Design scalable, AI-ready data architectures that support analytics, machine learning, and enterprise reporting.
- Establish patterns for batch, streaming, CDC, event-driven, and real-time data integration.
- Define standards for data ingestion, transformation, orchestration, testing, deployment, and operational support.
- Partner with engineering teams to ensure solutions are performant, scalable, maintainable, and cost-efficient.
- Guide architecture for Customer Cube and other strategic data products.
- Drive adoption of modern DataOps, DevOps, and platform engineering practices.
Cloud Infrastructure & Platform Architecture