--- title: 'AI Architect at Bottomline' canonical: 'https://feeny.ai/job/ai-architect-bottomline-india-zpn6sqaw126w' type: 'job' last_seen: '2026-10-25' --- # AI Architect at Bottomline - **Company:** Bottomline - **Location:** India - **Posted:** 2026-10-22 - **Last confirmed live:** 2026-10-25 - **Apply:** https://job-boards.greenhouse.io/bottomlinetechnologies/jobs/8860099002 ## Job description 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 Location India Reports To Level Individual Contributor / Architect (8+ years experience) ## Team Enterprise Data Services (EDS) Contract Permanent, Full-Time 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 - 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. Resilience, Disaster Recovery & Operational Readiness - 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. AI Governance & Responsible AI - 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. Architecture Leadership & Collaboration - 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. Business & Stakeholder Engagement - 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. ## Requirements Must Have - 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. Strong Preference - 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. ## Nice to Have - 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. Our Technology Stack Data & AI Platform Snowflake; Cortex AI; Cortex Agents; Cortex Search; Cortex Analyst; Snowpark; Dynamic Tables; Enterprise Data Warehouse Cloud & Infrastructure AWS; Infrastructure as Code; CI/CD Pipelines; Platform Automation; Monitoring & Observability Tooling Engineering Python; SQL; Git; DataOps; DevOps Analytics Power BI; Streamlit; Enterprise Semantic Models ## Why This Role Is Different - Shape the future of Bottomline's enterprise AI and data ecosystem. - Own architecture across AI, Data, Analytics, Cloud, and Platform Engineering. - Influence strategic technology and investment decisions. - Build reusable enterprise capabilities rather than one-off solutions. - Operate at the intersection of business strategy and technical execution. - Work directly with senior leadership on high-impact initiatives. - Drive the adoption of trusted, governed, and scalable AI solutions across the organisation. ## Your First 90 Days Days 1-30: Understand - Review the current data, AI, analytics, and platform architecture landscape. - Meet key stakeholders across Data Engineering, AI Engineering, Infrastructure, Security, Product, and Business teams. - Assess strategic programmes including Customer Cube and enterprise AI initiatives. - Identify architecture opportunities, gaps, and risks. Days 30-60: Define - Develop the enterprise AI and data architecture roadmap. - Publish initial architecture principles, standards, and governance processes. - Define target-state architectures for strategic AI and data platforms. - Establish architecture review and approval processes. Days 60-90: Enable - Launch architecture governance forums. - Support delivery teams with reference architectures and reusable patterns. - Define platform engineering, infrastructure, and observability standards. - Deliver initial architecture blueprints for strategic programmes. - Present the enterprise AI and data architecture roadmap to senior leadership. Success Measures After 12 months, success would include: - Enterprise AI and Data Architecture adopted across strategic initiatives. - Standardised architecture and engineering standards implemented across Data and AI teams. - Customer Cube established as a strategic enterprise data product. - Increased delivery velocity through reusable architecture patterns and shared services. - Reduced technical debt and improved platform maintainability. - Improved Snowflake performance, scalability, reliability, and cost efficiency. - Fully governed AI development lifecycle with measurable quality controls. - Mature disaster recovery and resilience capabilities across critical platforms. - Strong collaboration between Data Architecture, Data Engineering, AI Engineering, Infrastructure, and Security teams. - Demonstrable business outcomes delivered through scalable, trusted, and AI-enabled solutions. We welcome talent at all career stages and are dedicated to understanding and supporting additional needs. We're proud to be an equal opportunity employer, committed to creating an inclusive and open environment for everyone. ## About Bottomline ## Company Overview - **One-liner**: Bottomline helps businesses and financial institutions transform the way they pay and get paid with secure, connected payment, cash management, and fraud detection solutions. - **Entity Type**: Private (acquired by Thoma Bravo in 2022) - **Headquarters**: Portsmouth, New Hampshire, USA - **Founded**: 1989 - **Founders**: Not publicly available ## Core Business - Primary industry/industries: Business Payments, Financial Technology (FinTech), Cash Management, Payments Fraud & Compliance - Target customers: B2B – Financial institutions (banks, credit unions), mid-market to enterprise businesses (including Fortune 100 companies), and other organizations globally. - Mission or purpose statement: To transform the way businesses pay and get paid, driving impactful results for customers by reimagining business payments and delivering solutions that add to the bottom line. ## Products & Services - **Payments Hub**: A centralized platform to send payments to any bank worldwide, in any currency, ensuring governance and control. - **AP Automation**: Automates accounts payable processes from invoice to payment, enabling fast, revenue-generating Premium ACH and virtual card payments. - **Global Cash Management Hub**: Centralizes cash visibility, liquidity, FX, financing, and risk management for finance teams. - **Payments Fraud Defense**: A SaaS solution that detects and stops payment fraud and evolving threats in real-time. - **Enterprise Case Management**: Provides a single system of record for a holistic view of business risk to respond to threats faster. - **Digital Banking Platform**: A combined platform for payments, cash management, treasury management, and B2B payments network for financial institutions. - **Paymode Network**: A market-leading B2B payments network trusted by over 600,000 verified businesses for secure digital payments. - **Payments Processing**: Securely processes, reconciles, and manages data in financial transactions within and between banks. - **Sanctions Screening**: Real-time financial message sanctions screening for global compliance. - **Message Transformation & Enrichment**: An intelligent data transformation and workflow engine for meeting message standard compliance obligations. - **Payouts Automation**: Secure management of funds disbursements to suppliers, customers, and partners. - **Receivables Automation**: Streamlines the process of receiving funds into a business, supporting multiple payment methods. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed (privately held by Thoma Bravo). Thoma Bravo has more than $183 billion in assets under management. - **Key Metric (Total Funding)**: Not applicable (mature company, acquired). - **Notable Investors/Partners**: Thoma Bravo (owner), Swift (Top 3 Swift Services Provider). - **Growth Signals**: Moves more than $16 trillion in payments annually; serves nearly one million financial institutions and businesses in 92 countries; trusted by Fortune 100 companies; processes 50%+ of UK Direct Debit/Credit transactions; published 2025 ESG Report. ## Competitive Advantages - **Proprietary Network Effect**: Operates Paymode, a massive B2B payments network with over 600,000 verified businesses, creating a strong barrier to entry. - **End-to-End Platform**: Provides a unique, integrated suite spanning payments, cash management, treasury, and fraud compliance, reducing complexity for customers. - **Global Scale & Reliability**: Processes over $16 trillion in payments annually, with 35+ years of experience and deep integrations with global banking infrastructure. - **Strong Financial Backing**: Backed by Thoma Bravo, a leading software private equity firm, providing resources for long-term growth and stability. - **Trusted by the Enterprise**: Serves Fortune 100 companies and has a top-3 position as a Swift services provider. ## Strategic Focus - **Product Modernization**: Continuing to enhance its SaaS platform for payments, cash management, and fraud defense. - **Fraud & Compliance Leadership**: Investing heavily in real-time fraud detection and compliance solutions to combat evolving threats. - **Network Expansion**: Growing the Paymode B2B payments network to increase utility and value for all participants. - **Digital Banking**: Deepening its digital banking platform to strengthen its role as the primary technology partner for financial institutions. - **ESG**: Committed to sustainable operations and reporting, as evidenced by the release of its 2025 ESG Report. ## Why Work Here - **Mission-Driven Work**: Employees contribute to modernizing a critical, high-volume global financial infrastructure. - **Culture & Guiding Principles**: The company has a clearly articulated culture based on four principles: "Delight Customers," "Excellent Execution," "Create and Grow Sustained Business Value," and "Work With and for Each Other." - **Employee Wellbeing** ("One Bottomline"): Prioritizes flexibility and a supportive community, with empathetic leadership that supports employees through life milestones. Employee wellbeing takes precedence above all. - **Growth & Development**: Offers opportunities to learn and work with industry leaders across Engineering, Data, Product, Marketing, Finance, Sales, and more. They look for talent at all phases of their career. - **Global Team**: Describes itself as "One Global Team," working with passionate and motivated people to solve complex challenges. - **Work Environment**: A nurturing community that encourages open communication and leadership from any level, regardless of title or seniority. - **Diversity & Inclusion**: Is an Equal Opportunity and Affirmative Action Employer and participates in the E-Verify program. - **Perks**: While specific perks are not listed on the careers page, the company highlights employee wellbeing, flexibility, and a strong, supportive culture. ## Sources 1. [bottomline.com - About Us](https://www.bottomline.com/about) 2. [bottomline.com - Careers](https://www.bottomline.com/about/careers) 3. [LinkedIn - Bottomline](https://www.linkedin.com/company/bottomline-payments) 4. [bottomline.com - Explore Open Roles](https://www.bottomline.com/about/careers/jobs) 5. 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