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
The Program Modernization team at MasterCard drives transformation and champions modernization across technology, risk, and service operations. We establish the foundation for scalable programs, resilient systems and control governance that empowers transformation.
The mission of the Technology Modernization team is to enable all the Mastercard programs across the organization to thrive in an evolving regulatory environment by fostering a culture of strong technology controls and effective execution. The team designs and delivers innovative, data-driven solutions that fulfill assurance obligations and regulatory requirements by proactively identifying risks, build real-time tools that leverage technology to continuously test and monitor the control environment. These capabilities enables audit-ready compliance portal for inventorying, managing, testing, and evidencing technology controls.
Mastercard is committed to driving innovation through advanced technologies and data-driven insights. We are seeking a Lead Engineer to design and deliver scalable, enterprise-grade AI solutions that enhance our digital capabilities and customer experiences.
This role will focus on building intelligent, production-ready systems leveraging large language models (LLMs), knowledge bases with vector search, and modern cloud/data platforms, while ensuring alignment with Mastercard’s standards for security, performance, and reliability.
Role & Responsibilities
Design, develop, and deliver AI-powered solutions leveraging modern architectures, including LLM-based systems and retrieval-augmented generation (RAG)
Build and maintain enterprise knowledge bases with vector search capabilities, enabling semantic search and intelligent information retrieval
Develop LLM-driven applications using frameworks such as LangChain, including prompt engineering, chaining, and orchestration patterns
Implement and integrate solutions leveraging Model Context Protocols (MCP) or equivalent model interaction frameworks
Architect scalable and secure solutions across cloud and data ecosystems, including AWS, Cloudera, and Databricks
Collaborate cross-functionally with product, engineering, and data teams to translate business needs into AI-enabled solutions
Develop and maintain robust APIs and microservices to support AI applications and front-end integrations
Ensure solutions adhere to Mastercard’s standards for data governance, security, compliance, and operational excellence
Monitor and optimize model performance, reliability, and scalability in production environments
Contribute to technical design discussions, mentor junior engineers, and promote engineering best practices
All About You
Proven experience (10 to 15 years) in software engineering, with strong focus on AI/ML and distributed systems
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline
Strong proficiency in Python, with experience building scalable backend systems
Experience with Angular or similar frontend frameworks for building user-facing AI applications
Hands-on experience with LLM frameworks (e.g., LangChain) and building RAG-based systems
Expertise in designing knowledge bases with vector search and working with embedding models
Strong experience with cloud platforms, particularly AWS, and familiarity with Cloudera and Databricks ecosystems
Solid understanding of system design, APIs, and microservices architecture
Preferred Skills
Experience with Model Context Protocol (MCP) or similar AI orchestration frameworks
Experience with vector databases such as PGVector, GraphDB
Familiarity with MLOps practices, including CI/CD pipelines, monitoring, and lifecycle management
Knowledge of containerization and orchestration (Docker, Kubernetes)
Experience working in highly regulated, large-scale enterprise environments
Key Competencies
Strong problem-solving and analytical thinking
Ability to operate effectively in a collaborative, fast-paced environment
Excellent communication and stakeholder engagement skills
Demonstrated ownership and accountability for end-to-end delivery
Commitment to continuous learning and staying current with emerging AI technologies
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks must comply with Mastercard’s security policies and standards. Employees are responsible for maintaining the confidentiality, integrity, and availability of information.
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.
