Mastercard is a global technology leader in the payments industry, dedicated to connecting and powering an inclusive digital economy. With a presence in over 200 countries, we drive secure, simple, smart, and accessible transactions. Our mission is to ensure everyone, everywhere can prosper by leveraging innovation, partnerships, and networks to help individuals, businesses, and governments reach their full potential.

As a Principal Software Engineer, you will be instrumental in shaping the next generation of our Decision Management Platform. This role combines significant enterprise-level technical leadership with hands-on engineering, focusing on building core platform capabilities using modern AI-assisted development tools to enhance speed, quality, and adoption of best practices. You will explore disruptive technologies in real-time AI inferencing and decisioning to boost product effectiveness, business delivery, technical resilience, and reduce ownership costs. Collaborating with technology executives, senior leaders, and engineers, you will influence our overall AI & DPE technology strategy.

Key responsibilities include developing software, tooling, and platform capabilities, alongside designing and implementing large-scale distributed systems. You will create reusable services, patterns, and integrations, contributing to new product and prototype development from conception through validation.

Evaluate systems, frameworks, and tools based on quality, cost, latency, scalability, reliability, and maintainability, applying sound engineering judgment to distributed systems design and architectural trade-offs.

Leverage AI tools in daily engineering to solve real product and platform challenges, teaching and modeling the adoption of AI-assisted development, modern languages, and current practices. Enhance developer experience through automation, AI workflows, and platform thinking, advocating learnings and best practices across the organization.

Take ownership of and improve end-to-end customer experiences across service portfolios. Simplify and optimize architecture strategies, balancing cost, performance, and business value, while making informed trade-offs between competing priorities and technical constraints.

Lead architectural design for complex, enterprise-wide initiatives, driving organization-wide efforts to advance software engineering craftsmanship and best practices. Represent the organization through public speaking, technical blogs, and white papers, participating in principle-level architecture reviews and resolving enterprise-wide technical challenges.

Mentor engineers at all levels to foster technical growth and leadership, conduct technical interviews to enhance performance standards, and provide unbiased recommendations for promotions. Champion AI-assisted engineering as a standard practice, aligning it with organizational values.

We are seeking an accomplished engineer and leader passionate about solving complex, large-scale engineering challenges, particularly in high-speed streaming platforms or distributed systems with hyperscaler-level performance. Ideal candidates are AI-native engineers who embrace AI-assisted development, possess a streaming-first mindset, and have a track record of delivering impactful, production-ready systems.

Key attributes include being an innovation leader capable of building massive-scale systems with high availability, a champion for engineering culture driving best practices and transparency, and a collaborative team player working effectively across engineering and data science.

While expertise across all technical domains is not expected, candidates should demonstrate hands-on depth in one or more areas, including Decisioning Data & Feature Platforms, High-Throughput, Low-Latency & Real-Time Systems, AI & ML Systems, Decisioning Tooling & UX, and Cloud Infrastructure, Platform Engineering & DevOps.

Required qualifications include extensive experience in software engineering and technical leadership, proven delivery of large-scale distributed systems, expertise in cloud, AI/data platforms, and modern engineering practices, along with strong communication and mentorship skills. A Bachelor’s degree or equivalent is required, with an advanced degree being preferred. Telecommuting or remote work may be permissible based on company policies.