Vice President, Platform Architecture

We need to output HTML fragment with sections: headings

for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must include only sections that have real specific content. The posting includes: Title And Summary (but we shouldn't repeat job title as heading). There's a purpose paragraph, then Title And Summary (maybe we can treat as About the role). There's "Overview" etc. We need to extract sections. We need to remove boilerplate: purpose paragraph maybe considered "About the role"? Actually purpose is generic company description; could be considered About the role? The instruction: "Do NOT repeat the job title as a heading (the page already shows it)". So we can have heading "About the role" with purpose summary. We have responsibilities: "Key Responsibilities" with subpoints. We'll list each bullet as

. We have "Required Technical Expertise" and "Leadership Competencies". Those could be under Requirements or Qualifications? The posting has "Required Technical Expertise" and "Leadership Competencies". Also "Qualifications Required" and "Preferred". So we can have sections: Responsibilities, Requirements (maybe combine Required Technical Expertise + Leadership Competencies?), Qualifications (maybe required qualifications), Skills (maybe not separate), Benefits, Pay. We have Pay: "Pay Ranges New York City, New York: $254,000 - $407,000 USD". Also mention base salary competitive etc. So we can include Pay section. Benefits: description of benefits. So include Benefits. Schedule: not mentioned. So omit. We must not include sections with placeholder like "commensurate with experience". Not present. We must not include Job ID etc. We must preserve all substantive info; not invent. We need to output only HTML fragment, no /, no markdown fences. Let's craft:

About the role

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title And Summary Vice President, Platform Architecture Overview The Applied AI, Data & UX organization accelerates AI innovation and product delivery across Commercial & New Payment Flows (CNPF) through three pillars: This portfolio includes the Commercial Data Fabric, Agentic Development Frameworks, Unified UX Framework, Virtual C-Suite products, Commercial Business Directory, and other strategic AI capabilities.

But maybe we should keep purpose and then a brief about role. Could combine. Better: About the role: include purpose and overview. Now Responsibilities: list each bullet under "Key Responsibilities". We'll extract each bullet. Key Responsibilities sections: - Architecture Strategy & Governance - Define and own the long-term architecture strategy across AI, data, UX, and platform products. - Lead the architecture review process and establish standards for system design, integration, scalability, resiliency, and security. - Govern key architecture artifacts including technical standards, architecture decision records (ADRs), and integration patterns. - Identify and mitigate enterprise-level technology risks before they impact delivery. - AI, Data & Platform Architecture - Provide architectural oversight for the Commercial Data Fabric, including data pipelines, governance, feature platforms, analytics, and AI workloads. - Define architecture for agentic platforms, multi-agent orchestration, memory and context management, AI guardrails, evaluation frameworks, and observability. - Ensure AI products leverage common platforms and reusable services to prevent fragmentation and technical debt. - Guide architectural decisions across the full AI lifecycle, including data ingestion, training, deployment, monitoring, and optimization. - Engineering Excellence & Security - Establish standards for APIs, service boundaries, deployment architectures, data contracts, and AI evaluation frameworks. - Embed security, compliance, auditability, privacy, and regulatory requirements into architectural patterns from inception. - Drive adoption of security-by-design and resilience engineering practices. - Ensure adherence to PII, PCI, and governance requirements across global platforms. - Executive Leadership & Strategic Advisory - Serve as trusted advisor to senior executives on architecture strategy, technology investments, vendor selection, and build-versus-buy decisions. - Develop multi-year architecture roadmaps aligned to business priorities and Mastercard enterprise standards. - Translate complex technical trade-offs into clear business recommendations for executive stakeholders. - Represent the organization in architecture governance forums and external industry engagements. - Talent & Organizational Leadership - Mentor and develop principal architects and senior engineering leaders. - Foster a culture of architectural excellence, innovation, collaboration, and continuous learning. - Promote architecture as an enabling capability that accelerates product delivery and business outcomes. We'll put each as

under

. Now Requirements: we have "Required Technical Expertise" and "Leadership Competencies". Could combine under Requirements. List Required Technical Expertise bullets: - AI/ML Architecture: Enterprise-scale ML platforms, feature stores, model training infrastructure, deployment pipelines, monitoring, and evaluation frameworks. Production experience in AI/ML systems with a strong understanding of scalability, reliability, and model governance. - Data Platforms: Modern lakehouse architectures, data governance frameworks, batch and streaming processing, data contracts, and multi-region data management. Expertise in technologies such as Spark, Airflow, Delta Lake, DLT, and related ecosystems. - Agentic & AI Infrastructure: Multi-agent orchestration, context and memory management, policy enforcement, MCP integration, AI guardrails, evaluation pipelines, and observability. Strong understanding of enterprise AI platform architecture and operational governance. - Distributed Systems & Cloud Architecture: Cloud-native platforms, microservices, event-driven systems, Kubernetes, service meshes, APIs, and resilience engineering. Experience designing high-scale, mission-critical distributed systems in regulated environments. - Security & Compliance: Security-by-design principles, identity and access management, threat modeling, audit controls, PCI DSS, PII governance, and regulatory compliance frameworks. - UX Platform Architecture: Design systems, component libraries, design tokens, micro-frontends, experience telemetry, and scalable UX platform patterns. Leadership Competencies bullets: - Systems Thinking: Evaluates decisions based on enterprise-wide impact and long-term sustainability. - Technical Credibility: Influences through deep expertise and sound architectural judgment. - Executive Communication: Translates technical complexity into business outcomes and risk-based decisions. - Strategic Foresight: Anticipates risks and opportunities before they emerge. - Collaborative Leadership: Drives alignment across product, engineering, architecture, and business teams. - Inclusive Leadership: Encourages diverse perspectives and develops technical talent globally. Now Qualifications: "Qualifications Required" and "Preferred". We'll list required qualifications as bullet list. Required Qualifications: - 15+ years of software engineering experience with 8+ years in enterprise, platform, or systems architecture roles. - 5+ years of senior technology leadership experience managing architects and engineering leaders within global, matrixed organizations. - Proven track record developing and executing architecture strategies across complex, multi-platform environments. - Deep expertise in AI/ML engineering, data platforms, distributed systems, cloud-native architecture, and enterprise governance. - Experience within financial services, payments, fintech, or other highly regulated industries. - Demonstrated success influencing executive stakeholders and driving decisions through technical leadership rather than formal authority. - Experience leading strategic platform evaluations, vendor assessments, and build-versus-buy decisions. - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience. Preferred Qualifications: - Experience building large-scale AI products, commercial data platforms, or agentic AI systems. - Knowledge of payments technology ecosystems and enterprise-scale platform architectures. - Expertise in AWS, Azure, GCP, Kubernetes, and multi-region deployments. - Experience Establishing Or Leading Architecture Review Board Functions. - Industry thought leadership through publications, conference speaking, standards participation, or open-source contributions. - Master's degree in Computer Science, Engineering, or MBA. Now Benefits: paragraph about benefits. We have: "Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations." We'll put that as

under Benefits. Pay: "Pay Ranges New York City, New York: $254,000 - $407,000 USD". Also earlier: "In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience." We'll include Pay section with that info. Now ensure we don't repeat job title as heading. We didn't. Now output HTML fragment. Let's construct:

About the role

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title And Summary Vice President, Platform Architecture Overview The Applied AI, Data & UX organization accelerates AI innovation and product delivery across Commercial & New Payment Flows (CNPF) through three pillars: This portfolio includes the Commercial Data Fabric, Agentic Development Frameworks, Unified UX Framework, Virtual C-Suite products, Commercial Business Directory, and other strategic AI capabilities.

Responsibilities

• Architecture Strategy & Governance: Define and own the long-term architecture strategy across AI, data, UX, and platform products. Lead the architecture review process and establish standards for system design, integration, scalability, resiliency, and security. Govern key architecture artifacts including technical standards, architecture decision records (ADRs), and integration patterns. Identify and mitigate enterprise-level technology risks before they impact delivery.
• AI, Data & Platform Architecture: Provide architectural oversight for the Commercial Data Fabric, including data pipelines, governance, feature platforms, analytics, and AI workloads. Define architecture for agentic platforms, multi-agent orchestration, memory and context management, AI guardrails, evaluation frameworks, and observability. Ensure AI products leverage common platforms and reusable services to prevent fragmentation and technical debt. Guide architectural decisions across the full AI lifecycle, including data ingestion, training, deployment, monitoring, and optimization.
• Engineering Excellence & Security: Establish standards for APIs, service boundaries, deployment architectures, data contracts, and AI evaluation frameworks. Embed security, compliance, auditability, privacy, and regulatory requirements into architectural patterns from inception. Drive adoption of security-by-design and resilience engineering practices. Ensure adherence to PII, PCI, and governance requirements across global platforms.
• Executive Leadership & Strategic Advisory: Serve as trusted advisor to senior executives on architecture strategy, technology investments, vendor selection, and build-versus-buy decisions. Develop multi-year architecture roadmaps aligned to business