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 (Agentic workflows/APIs)
Overview
Mastercard is seeking a highly skilled and passionate Tech Lead to drive the next generation of platform modernization, API transformation, cloud-native engineering, agentic workflow solutions, and AI-enabled product capabilities.
The ideal candidate is a hands-on technical leader who can architect and deliver scalable enterprise systems while mentoring engineering teams, influencing technical strategy, and driving innovation across multiple initiatives.
This role requires deep expertise in distributed systems, APIs, cloud technologies, AI-powered engineering, data platforms, and software delivery at scale. The successful candidate will play a critical role in shaping the future of Mastercard's intelligent platforms by combining strong technical leadership with exceptional execution capabilities.
Role & Responsibilities
Technical Leadership
• Lead end-to-end delivery of complex engineering initiatives.
• Define technical architecture, engineering patterns, solution roadmaps, and development standards.
• Drive technical design reviews, architecture discussions, and engineering best practices.
• Guide teams in building scalable, secure, resilient, and maintainable platforms.
• Evaluate emerging technologies and recommend strategic adoption opportunities.
• Influence technical roadmaps and long-term platform strategy.
Software Engineering
• Design and develop enterprise-grade backend services, APIs, and distributed systems using Java and Spring Boot.
• Build scalable, high-availability microservices and cloud-native applications.
• Design and implement secure, high-performance RESTful APIs and integrations.
• Ensure software quality through code reviews, automated testing, and engineering governance.
• Drive modernization, automation, and platform engineering initiatives.
Agentic Workflows & AI Enablement
• Design and implement agent-driven workflows and intelligent automation solutions.
• Integrate AI powered capabilities into engineering and operational processes.
• Collaborate with business and engineering stakeholders to identify AI-enabled use cases.
• Establish best practices for responsible AI adoption within software delivery lifecycles.
• Drive adoption of AI-assisted development practices to improve engineering productivity and quality.
Cloud, Platform & Data Engineering
• Design, develop, and deploy solutions on AWS.
• Build reusable frameworks, platforms, and engineering accelerators.
• Enable Infrastructure as Code (IaC) and automation-first engineering practices.
• Design and support scalable ETL, analytics, and data processing solutions.
• Build event-driven and data-intensive applications using modern architecture patterns.
• Partner with DevOps teams to improve deployment reliability, scalability, and operational maturity.
Operational Excellence
• Champion observability, monitoring, alerting, reliability, and performance engineering practices.
• Lead incident management, troubleshooting, and root-cause analysis activities.
• Drive continuous improvement initiatives focused on availability, performance, resiliency, and security.
• Ensure compliance with Mastercard engineering, risk, and security standards.
Team Leadership
• Mentor and coach software engineers and senior engineers.
• Support hiring, onboarding, and technical skill development.
• Foster a culture of accountability, innovation, ownership, and continuous learning.
• Collaborate effectively across Product, Architecture, Security, Operations, and Engineering teams.
• Develop future technical leaders and promote engineering excellence.
Required Qualifications
Education
• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
Experience
• 8+ years of software engineering experience.
• Proven track record delivering enterprise-scale software solutions.
• Experience leading cross-functional engineering initiatives.
• Experience building cloud-native and distributed systems at scale.
• Strong experience mentoring engineers and driving engineering excellence.
Technical Skills
Category Technologies / Expertise
Programming Languages Java (8+), Python
Backend Engineering Spring Boot, Spring Cloud, Microservices, REST APIs, OpenAPI/Swagger, API Lifecycle Management, Distributed Systems
Architecture & Design System Design, Object-Oriented Design, Design Patterns, Domain Driven Design (DDD), Event-Driven Architecture, CQRS, Event Sourcing, Hexagonal/Clean Architecture
Cloud Technologies AWS EC2, ECS, EKS, Lambda, S3, API Gateway, IAM, SNS, SQS, RDS
Databases Oracle, PostgreSQL, MongoDB, NoSQL Databases
Event Streaming & Messaging Kafka, Axon Framework, Event Streaming Platforms
DevOps & Platform Engineering Git, GitHub, Jenkins, Maven, Gradle, CI/CD Pipelines, Infrastructure as Code (IaC), Platform Engineering
Monitoring & Observability Splunk, Dynatrace, OpenTelemetry, Distributed Tracing, Application Monitoring, Logging & Alerting
Security OAuth2, JWT, Secure API Development, Secure SDLC, Authentication & Authorization, Encryption Standards, Secure Coding Practices
AI & Agentic Engineering GitHub Copilot, Microsoft Copilot, Agentic
Engineering Practices
The ideal candidate demonstrates:
• Strong object-oriented design and architecture skills.
• Expertise in scalable system design and distributed architecture.
• Experience with design patterns and modern engineering practices.
• Expertise in unit, integration, performance, and automated testing.
• Strong knowledge of CI/CD, DevOps, and automation-first development.
• Experience working in Agile product development environments.
• Strong focus on reliability, observability, security, and performance optimization.
Preferred Qualifications
• Experience building AI-powered or agentic applications.
• Familiarity with LLM platforms, GenAI, MCP, Copilot, or related technologies.
• Experience with event-streaming platforms such as Kafka.
• Experience with AWS services including Lambda, ECS/EKS, API Gateway, S3, CloudWatch, and IAM.
• Knowledge of Infrastructure as Code tools such as Terraform.
• Experience with observability platforms such as Splunk and Dynatrace.
• Experience with Databricks, Snowflake, or modern analytics platforms.
• Experience building enterprise API products and developer ecosystems.
• Experience leading cloud transformation and modernization programs.
• Payments, fintech, or financial services industry experience.
Success Measures
The successful candidate will:
• Deliver scalable and secure platform solutions aligned with business objectives.
• Accelerate adoption of agentic and AI-enabled engineering capabilities.
• Improve engineering productivity, quality, operational excellence, and platform reliability.
• Mentor engineers and grow overall team capability.
• Drive technical innovation while maintaining strong delivery execution.
• Influence architecture and technology strategy across the organization.
• Champion engineering excellence and modern software development practices.
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.