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 archi ... (truncated, view full listing at source)