Lead Software Engineer

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

Lead Software Engineer

Overview

Mastercard Dynamic Yield is looking for a Senior Software Architect to join our engineering organization and help shape the technical future of our platforms. This role is focused on owning end-to-end architecture for large-scale, cloud-native systems, while playing a hands-on leadership role in adopting and running agentic GenAI systems in production.

You will act as a technical focal point across teams, driving architectural coherence, accelerating technical feasibility for products, and ensuring our systems are scalable, secure, and future-ready. This is a senior, impact-driven role for an architect who leads through deep technical expertise rather than people management.

Role - Key Responsibilities

Own and evolve end-to-end architecture for large-scale, cloud-native platforms and distributed systems

Act as a technical focal point across multiple engineering teams, influencing technical direction and driving alignment without direct authority — building consensus through credibility and communication

Partner with Product to proactively shape the long-term roadmap, bringing technical perspective into strategic planning

Break down complex business and technical problems into clear system components, interfaces, and interactions

Define and uphold architectural principles across scalability, resilience, security, and operability

Architect and guide AWS-first platforms, including microservices, event-driven, and asynchronous systems

Establish strong API design, versioning, and data contract practices across the platform

Design, build, and run agentic GenAI systems in production, including orchestration, tool usage, planning, and state management

Define production-grade practices for AI systems: observability, evaluation, reliability, safety, and cost control

Drive architectural reviews, technical decision-making, and trade-off discussions

Partner closely with Engineering, Product, and Data Science to accelerate technical feasibility and delivery

Contribute to long-term technical strategy, platform evolution, and selective POCs where they create clear value

All About You

10+ years of professional software engineering experience, with time in architecture-focused roles

Proven track record designing and operating large-scale distributed systems in production

Strong, hands-on AWS experience (required)

Deep knowledge of cloud-native and backend systems: microservices, APIs, events streaming, data flows

Hands-on experience building and running agentic AI / GenAI systems in production (required)

Including LLM-based agents, tool usage, planning, and stateful workflows

Strong understanding of system design trade-offs, scalability, reliability, and operational concerns

Ability to clearly explain complex technical concepts to both technical and non-technical audiences

Strongly Preferred

Experience with RAG-based, multi-agent, or autonomous/semi-autonomous agent systems

Experience integrating AI systems with existing platforms and APIs

Background working closely with Data Science and ML teams

Experience influencing architecture across multiple teams and products

Familiarity with data platforms and pipelines (e.g., streaming, analytics, ML data flows)

What Makes This Role Impactful

You will shape how platform and agentic AI systems are built responsibly and at scale

You will act as a driver of technical feasibility and innovation, not a gatekeeper

Your architectural decisions will directly impact system reliability, product velocity, and long-term business value

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard’s security policies and practices;

• Ensure the confidentiality and integrity of the information being accessed;

• Report any suspected information security violation or breach, and

• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.