AI Architect

Overview

Define and lead the future-state architecture for Bottomline's Data, Analytics, AI, and Cloud Platforms, combining AI, enterprise data, data engineering and cloud platform architecture, in partnership with the Data Architect.

What you'll 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 and determine their applicability to Bottomline.
• Create architectural blueprints that enable scalable and governed AI adoption across the organisation.
• 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.
• Define cloud architecture patterns supporting Snowflake, AI workloads, data pipelines, and analytics services.
• Establish standards for CI/CD, Infrastructure as Code (IaC), platform automation, and deployment frameworks.
• Design scalable and resilient architectures capable of supporting enterprise AI workloads.
• Define standards for observability, monitoring, logging, alerting, and platform health management.
• Support infrastructure modernisation and platform optimisation initiatives.
• Partner with Infrastructure and Security teams to ensure enterprise-grade operational practices.
• Define architectural standards for disaster recovery, backup, resilience, and business continuity.
• Ensure critical data and AI platforms have documented and tested recovery capabilities.
• Guide architecture decisions related to high availability and system resilience.
• Support audit, risk, compliance, and security initiatives through robust architectural controls.
• Define operational readiness requirements for production AI and data services.
• Establish enterprise AI governance frameworks.
• Define standards for model evaluation, monitoring, explainability, fairness, and risk management.
• Create architectural guardrails for AI development and deployment.
• Collaborate with Legal, Compliance, Security, and Governance teams to ensure regulatory alignment.
• Drive adoption of responsible AI principles across all AI initiatives.
• Partner closely with the Data Architect to develop a unified enterprise data and AI architecture strategy.
• Participate in architecture governance forums and design reviews.
• Define and maintain architecture standards across Data Engineering, AI Engineering, Analytics, and Platform Engineering.
• Mentor engineers and architects on best practices and emerging technologies.
• Review and approve solution architectures for major strategic initiatives.
• Act as a trusted advisor to business and technology leadership.
• Translate business strategy into executable technology roadmaps.
• Communicate complex technical concepts to both technical and non-technical audiences.
• Support organisational AI adoption and transformation initiatives.

What you'll need

• 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).
• Cloud Architecture certification(s).
• Experience presenting architecture strategy to Executive Leadership Teams.
• Experience supporting enterprise AI transformation programmes.
• Knowledge of Data Mesh, Lakehouse, or modern distributed data architecture patterns.

Details

• Location: India.
• Individual Contributor / Architect role; reports to the Senior Director of AI & Data Services, with a dotted-line relationship to the Data Architect.
• Permanent, full-time.