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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. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Role Overview
You will design and build the next-generation Decision Management Platform: the real-time system that scores and approves billions of payment transactions. The role is hands-on. You will write code, run prototypes, and use AI coding tools every day to ship faster and at higher quality. You’ll be joining a high‑growth team that’s actively expanding to meet increasing scale and impact.
You will work directly with senior engineers, architects, and product managers to deliver features that make the platform faster, more reliable, and cheaper to run.
Key Responsibilities
Build the Platform
•Write production code for services, tooling, and platform features.
•Design and implement components of large distributed systems.
•Build reusable services, libraries, and integrations.
•Take prototypes from idea to working software.
Make Sound Technical Calls
•Pick the right frameworks, libraries, and tools by weighing quality, cost, latency, and reliability.
•Make clear trade-offs in the systems you own and explain them to your team.
Use AI Tools and Help Others Do the Same
•Use AI coding tools as your default way of working.
•Share patterns, demos, and tips with your team so they get the same leverage.
•Automate the boring parts of development.
Improve What You Own
•Make the customer experience better across the services you work on.
•Simplify designs to cut cost or latency without losing capability.
•Pay down technical debt, fix resiliency gaps, and close operational risks.
Work Across Teams
•Contribute to designs that span multiple services.
•Give useful feedback in design and code reviews.
Grow the Team
•Mentor peers and junior engineers.
•Interview candidates and help raise the hiring bar.
What We're Looking For
•You ship. A track record of delivering real features in real distributed systems at scale.
•You build for scale. Hands-on experience with high-throughput, low-latency systems — ideally streaming or real-time decisioning.
•You thrive in startup-mode teams. Experience at a startup or in a startup-like environment inside a larger company: small teams, shifting priorities, owning things end-to-end.
•You're polyglot and curious. Comfortable working in several languages and eager to pick up new ones, frameworks, and tools as the problem demands.
•You use AI tools well. Claude Code, Copilot, or similar are part of how you work, not something you've tried once.
•You write clear code and clear words. You can explain a design to an engineer and a product manager.
•You care about the craft. Tests, observability, and clean interfaces are not optional for you.
•You collaborate. You work well with engineers, data scientists, and product partners.
Technical Domains
You won't need all of these. Show real hands-on experience in several.
Decisioning Data & Features
•Data platforms for decisioning: lakehouses, delta lakes, distributed logs.
•Feature platforms: defining, validating, and serving features for batch and real-time use.
•Data models for events, features, reference data, labels, and outcomes.
•Data contracts, lineage, and quality checks.
High-Throughput, Low-Latency Systems
•Event streaming and high-volume pipelines.
•Distributed caches and in-memory data grids.
•Sub-second transaction processing.
•Rules engines.
AI & ML Systems
•Training, deploying, refreshing models, and serving low-latency inference.
•LLM integration, prompt engineering, and agentic patterns.
•Model monitoring: drift, feedback loops, production reliability.
Decisioning Tooling
•Authoring, testing, and deploying business rules.
•Tools that let authors validate rules and models before they ship.
•Operator workflows: approvals, observability, and explaining live decisions.
Cloud & DevOps
•AWS and cloud-native patterns.
•CI/CD, automation, observability, GitOps.
Requirements
•Several years of software engineering experience with real contributions to complex systems or shared platforms.
•Hands-on experience with distributed systems running at high throughput and sub-second latency. You understand multi-region availability, consistency, backpressure, and capacity.
•Solid grasp of modern software engineering practices, cloud-native architectures, and AI/data platforms.
•Clear communicator who works well across teams.
•Bachelor's degree in Computer Science, Software Engineering, or a related field — or equivalent experience. Advanced degrees are a plus, not a requirement.Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [email protected] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
Job Description
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 EngineerAbout MastercardMastercard 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. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Role Overview
You will design and build the next-generation Decision Management Platform: the real-time system that scores and approves billions of payment transactions. The role is hands-on. You will write code, run prototypes, and use AI coding tools every day to ship faster and at higher quality. You’ll be joining a high‑growth team that’s actively expanding to meet increasing scale and impact.
You will work directly with senior engineers, architects, and product managers to deliver features that make the platform faster, more reliable, and cheaper to run.
Key Responsibilities
Build the Platform
•Write production code for services, tooling, and platform features.
•Design and implement components of large distributed systems.
•Build reusable services, libraries, and integrations.
•Take prototypes from idea to working software.
Make Sound Technical Calls
•Pick the right frameworks, libraries, and tools by weighing quality, cost, latency, and reliability.
•Make clear trade-offs in the systems you own and explain them to your team.
Use AI Tools and Help Others Do the Same
•Use AI coding tools as your default way of working.
•Share patterns, demos, and tips with your team so they get the same leverage.
•Automate the boring parts of development.
Improve What You Own
•Make the customer experience better across the services you work on.
•Simplify designs to cut cost or latency without losing capability.
•Pay down technical debt, fix resiliency gaps, and close operational risks.
Work Across Teams
•Contribute to designs that span multiple services.
•Give useful feedback in design and code reviews.
Grow the Team
•Mentor peers and junior engineers.
•Interview candidates and help raise the hiring bar.
What We're Looking For
•You ship. A track record of delivering real features in real distributed systems at scale.
•You build for scale. Hands-on experience with high-throughput, low-latency systems — ideally streaming or real-time decisioning.
•You thrive in startup-mode teams. Experience at a startup or in a startup-like environment inside a larger company: small teams, shifting priorities, owning things end-to-end.
•You're polyglot and curious. Comfortable working in several languages and eager to pick up new ones, frameworks, and tools as the problem demands.
•You use AI tools well. Claude Code, Copilot, or similar are part of how you work, not something you've tried once.
•You write clear code and clear words. You can explain a design to an engineer and a product manager.
•You care about the craft. Tests, observability, and clean interfaces are not optional for you.
•You collaborate. You work well with engineers, data scientists, and product partners.
Technical Domains
You won't need all of these. Show real hands-on experience in several.
Decisioning Data & Features
•Data platforms for decisioning: lakehouses, delta lakes, distributed logs.
•Feature platforms: defining, validating, and serving features for batch and real-time use.
•Data models for events, features, reference data, labels, and outcomes.
•Data contracts, lineage, and quality checks.
High-Throughput, Low-Latency Systems
•Event streaming and high-volume pipelines.
•Distributed caches and in-memory data grids.
•Sub-second transaction processing.
•Rules engines.
AI & ML Systems
•Training, deploying, refreshing models, and serving low-latency inference.
•LLM integration, prompt engineering, and agentic patterns.
•Model monitoring: drift, feedback loops, production reliability.
Decisioning Tooling
•Authoring, testing, and deploying business rules.
•Tools that let authors validate rules and models before they ship.
•Operator workflows: approvals, observability, and explaining live decisions.
Cloud & DevOps
•AWS and cloud-native patterns.
•CI/CD, automation, observability, GitOps.
Requirements
•Several years of software engineering experience with real contributions to complex systems or shared platforms.
•Hands-on experience with distributed systems running at high throughput and sub-second latency. You understand multi-region availability, consistency, backpressure, and capacity.
•Solid grasp of modern software engineering practices, cloud-native architectures, and AI/data platforms.
•Clear communicator who works well across teams.
•Bachelor's degree in Computer Science, Software Engineering, or a related field — or equivalent experience. Advanced degrees are a plus, not a requirement.Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [email protected] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
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.
Pay Ranges