
Global payments and technology company
Lead Software Engineer at Mastercard
About the role
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
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Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
Required skills
Software architecture
Distributed systems
Cloud-native systems
Technical leadership
System design
Scalability
Security
Cross-team alignment
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About Mastercard

Mastercard
PublicA financial network that processes payments between banks and cardholders
10,001+
Employees
Purchase
Headquarters
$360B
Valuation
Reviews
10 reviews
3.8
10 reviews
Work-life balance
2.8
Compensation
4.1
Culture
4.2
Career
3.4
Management
3.1
72%
Recommend to a friend
Pros
Great team culture and supportive colleagues
Excellent benefits and compensation
Training and development opportunities
Cons
Work-life balance challenges and long hours
High pressure and stress during peak times
Management issues and lack of direction
Salary Ranges
51 data points
Junior/L3
Director
Junior/L3 · Data Engineer
5 reports
$137,800
total per year
Base
$106,000
Stock
-
Bonus
-
$107,900
$166,918
Interview experience
3 interviews
Difficulty
3.3
/ 5
Duration
14-28 weeks
Offer rate
33%
Experience
Positive 33%
Neutral 34%
Negative 33%
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Super Day/Final Round
6
Offer
Common questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
Past Experience
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