Senior 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

Senior Software Engineer

Overview

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.
Mastercard Payment Networks Technology team is looking for a Sr. Software Engineer to drive our customer experience strategy forward by consistently innovating and problem-solving. The ideal candidate is passionate about the customer experience journey, highly motivated, intellectually curious, analytical, and possesses an entrepreneurial mindset.

Role
• Independently translate business and system requirements into pragmatic designs, modular code, rapid AI proofs of concept (PoCs), minimum viable products (MVPs), and production-ready applications.
• Build AI-powered applications and backend services using hosted foundation-model APIs, SDKs, enterprise data, and reusable services; evaluate ideas quickly and recommend whether they should progress, pivot, or stop.
• Build end-to-end Retrieval-Augmented Generation (RAG) solutions covering ingestion, chunking, embeddings, vector or hybrid retrieval, reranking, grounding, citations, and permission-aware responses.
• Build and integrate Model Context Protocol (MCP) clients and servers that expose enterprise tools, prompts, resources, data, and services through standardized, governed, and auditable interfaces.
• Develop agentic workflows using tool calling, orchestration, state and memory patterns, structured outputs, guardrails, confidence controls, output validation, and human-in-the-loop approvals.
• Use Claude, GitHub Copilot, and comparable AI-assisted engineering tools hands-on to accelerate discovery, prototyping, coding, testing, documentation, and code review while protecting confidential information and validating generated output.
• Define engineering standards, evaluation criteria, and automated validation processes for AI-powered applications and developer productivity solutions, ensuring high quality, reliability, security, maintainability, and operational excellence.
• Productionize validated AI solutions using secure coding, automated testing, CI/CD, configuration management, observability, resilience, performance optimization, and rollback strategies.
• Embed security, privacy, compliance, Responsible AI, least-privilege access, role-based authorization, secrets management, data minimization, content safety, and auditability into solution design.
• Collaborate with product owners, architects, platform engineers, quality engineers, domain experts, and business stakeholders to resolve roadblocks and deliver high-quality outcomes in a fast-paced Agile environment.

All About You
Must-have qualifications
• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent practical experience.
• Strong software engineering experience delivering secure, reliable enterprise applications, APIs, backend services, or distributed systems, with the independence expected of a Senior Software Engineer.
• Hands-on experience building AI-enabled applications using modern programming languages, enterprise data, APIs, and AI-assisted development tools.
• Practical experience with LLM applications, RAG, agentic workflows, or similar applied AI patterns.
• Hands-on experience using AI application frameworks, hosted model services, and relevant SDKs to build and integrate enterprise AI solutions.
• Strong understanding of API design, distributed systems, automated testing, secure development, CI/CD, and production support practices.
Preferred qualifications
• Experience in payments, high-volume transaction processing, or other highly available and regulated technology environments.
• Familiarity with cloud-native platforms, observability, resiliency, and Responsible AI practices.

Skills, Tools & Technologies
Must have:
• Core: Python or another modern programming language, experience with SQL and other relational or NoSQL databases, backend services and distributed systems for integrating enterprise data, AI capabilities, and resilient high-volume transaction workflows, strong debugging skills, Git, and automated testing.
• AI workflows and quality: LLM application development and RAG, with emphasis on prompts and agent workflows, and guardrails and evaluation logic.
• AI platforms and frameworks: Knowledge of Anthropic APIs, AWS Bedrock, Azure OpenAI, or equivalent hosted-model services, and LangChain, LangGraph, or equivalent SDKs.
Good To Have:
• Enterprise application engineering: REST/gRPC APIs, secure coding, and CI/CD practices that automate testing and evaluation and enable reliable AI application releases.
• Cloud-native reliability and operations: AWS or Azure, Docker, Kubernetes, observability, security controls, and high-availability application design.
• Domain technology stack: C/C++, SQL, Unix/Linux, sockets, inter-process communication (IPC), shared memory, and microservices.

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.