Sr. Principal Software Engineer

Overview of Mastercard and the Role

Mastercard empowers economies globally, enabling secure, simple, smart, and accessible digital payments across 200+ countries. As a Sr. Principal Software Engineer within the AI & Data Platform Engineering organization, you will provide critical technology leadership and strategic influence for the next generation Decision Management Platform. This role involves driving innovation and engineering excellence, focusing on leveraging disruptive real-time AI inferencing and decisioning technologies to enhance product effectiveness, agility, resilience, scalability, and cost efficiency. You will collaborate closely with technology executives, senior leaders, and engineers to shape the overall AI & DPE technology strategy.

Key Responsibilities

• Enterprise Architecture & Technical Leadership: Lead architectural design for complex, enterprise-wide initiatives involving multiple services and high-scale decisioning workloads. Define service interactions, data flows, dependency models, and architecture policies to ensure scalability, resiliency, and security. Partner with business and product leaders to architect new services for innovative Mastercard products.
• Customer Experience & Platform Strategy: Improve the end-to-end experience for internal and external customers. Simplify and optimize architecture strategies, balancing cost efficiency, performance, and functional requirements. Apply expert-level technical judgment to guide large-scale design trade-offs.
• Thought Leadership & Influence: Drive engineering best practices, software craftsmanship, and architectural rigor. Represent engineering through technical presentations, publications, and knowledge-sharing. Participate in Principal-level architecture reviews to address complex enterprise-wide challenges.
• Collaboration & Knowledge Sharing: Work across organizational boundaries to identify integration opportunities, reduce redundancy, and drive platform cohesion. Mentor engineers and rising architects, promoting knowledge sharing across communities.
• Talent & Culture: Conduct deep technical interviews to identify top engineering talent. Champion behaviors that support a culture of excellence, inclusivity, and accountability.

Qualifications

The ideal candidate will have extensive hands-on software engineering experience building and architecting distributed systems or real-time processing platforms. This includes deep architectural expertise in large-scale, high-throughput systems, end-to-end service design, data flows, and dependency modeling. Strong experience with cloud and data platform technologies, real-time decisioning, and enterprise-grade system reliability and security is essential. Prior work integrating AI/ML or analytic models into production systems, especially for real-time or near real-time workloads, is required. Demonstrated ability to lead complex technical designs, influence cross-functional engineering teams, and guide platform-wide architectural decisions is critical, alongside strong problem-solving, communication, and technical leadership skills, including mentoring senior engineers.

Preferred Qualifications

• Experience with high-volume transactional systems, business rules management platforms, or real-time streaming pipelines.
• Background working with large in-memory data grids, rule engines, or decisioning engines.
• Experience contributing to organizational standards, technical publications, or architecture communities of practice.
• Prior work in environments involving regulated data, compliance constraints, or high-availability requirements.

Key skills/competency

• Enterprise Architecture
• Distributed Systems
• Real-time Processing
• AI/ML Integration
• Cloud Platforms
• Data Platform Engineering
• High-throughput Systems
• Decision Management
• Technical Leadership
• System Scalability