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
Manager, Software Engineering, AI Foundations
Overview
Mastercard is seeking a Manager, Software Engineering to lead the design, development, and delivery of AI platform capabilities that enable intelligent products and agentic experiences across B&MI.
This role combines people leadership, technical ownership, and cross-functional delivery accountability. You will lead one or more engineering teams building reusable AI platform services, integration patterns, and production capabilities. You'll also shape architecture, enforce engineering standards, and make sure solutions meet Mastercard requirements for security, reliability, responsible AI, and governance. This role is ideal for a hands-on engineering leader who can scale teams, shape AI platform direction, and help product teams move AI solutions from experimentation into production.
Role
- Lead, coach, and develop one or more teams of software engineers by setting clear goals, managing performance, and creating development plans aligned to individual and organizational objectives.
- Build a strong engineering culture focused on ownership, quality, accountability, and continuous improvement, and partner with leadership on hiring, team composition, and long-term planning.
- Guide teams through change and ambiguity, connecting team priorities to broader business and enterprise goals.
- Own end-to-end delivery of complex initiatives across multiple systems, services, or teams. This includes defining roadmaps and priorities with Product and stakeholders, managing dependencies and risks, and resolving cross-team blockers.
- Establish execution frameworks for planning, estimation, and tracking that enable predictable, high-quality delivery.
- Lead development of scalable AI platform services and reusable capabilities that support AI-powered products, intelligent workflows, and agentic systems, designed for secure integration, reliability, observability, and reuse across teams.
- Drive production integration of AI capabilities, including model inference, LLM-based services, orchestration, enterprise data and system connectivity, evaluation, and guardrails.
- Promote shared engineering patterns and standardization to speed up delivery and reduce duplication across teams.
- Define and evolve AI platform architecture in line with enterprise standards for scalability, security, interoperability, and maintainability, and translate complex product, AI, and integration requirements into robust system designs.
- Evaluate new technologies and lead adoption decisions based on business value, technical fit, and long-term sustainability, balancing near-term delivery with platform strategy and technical debt.
- Ensure systems meet Mastercard standards for reliability, security, compliance, performance, and observability, and establish best practices for AI evaluation, guardrails, lifecycle management, and production monitoring.
- Own production health, including troubleshooting, incident management, root cause analysis, and continuous improvement, and drive adoption of code review, CI/CD, automated testing, and secure coding practices.
- Collaborate with AI Engineers, Data Scientists, Product Managers, Architects, and platform teams to deliver integrated AI solutions, and communicate technical strategy, risks, and progress clearly to leadership and partners.
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All About You
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
- Proven experience leading software engineering teams that deliver shared platforms, distributed systems, or AI-enabled capabilities.
- Strong background in distributed systems, object-oriented programming, and backend engineering (e.g., Java, Python, or similar).
- Hands-on depth in software design and architecture, data structures, code review, and performance engineering.
- Experience designing or integrating production AI capabilities, including LLM-based services, agentic systems, workflow orchestration, model APIs, or related platform patterns.
- Demonstrated ability to drive architecture decisions and influence system design across teams.
- Experience owning delivery of complex, cross-team initiatives end to end.
- Strong understanding of operational practices, including observability, unit, functional, and integration testing, reliability, incident response, system performance, and secure software development.
- Proven people management experience, including performance management, mentoring, and team development.
Preferred Skills
- Experience building reusable platform capabilities used by multiple product or engineering teams.
