Lead Software Engineer

Lead Software Engineer

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. Role overview You will lead the design and development of the next-generation Decision Management Platform: the real-time system that scores and approves billions of payment transactions. The role is deeply hands-on while also requiring technical leadership. You will write code, shape architecture, drive prototypes, and use AI coding tools every day to move faster and raise engineering quality across the team. You will work directly with engineers, architects, product managers, and senior stakeholders to deliver capabilities that make the platform faster, more reliable, more secure, and cheaper to run. You will influence technical direction, guide design decisions across teams, and help turn business goals into scalable engineering solutions. You'll be joining a high‑growth team that's actively expanding to meet increasing scale and impact.

Key responsibilities

• Build the platform
• Lead the design and development of production services, tooling, and platform capabilities.
• Own key components of large distributed systems, from architecture and data structures through implementation, testing, deployment, and operation.
• Build an enterprise-critical platform that support multiple applications and teams
• Take ideas from concept to working software and help others do the same.
• Provide thought leadership for implementing the latest and best-in-class components and design patterns.

Make sound technical calls

• Make strong technical decisions across frameworks, libraries, data structures, and platform patterns, balancing quality, cost, latency, security, reliability, and maintainability.
• Shape software architecture and design standards for the systems you own and the broader platform.
• Use code and design reviews to improve quality, readability, and maintainability.

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

• Improve the reliability, observability, and supportability of the services and workflows you own.
• Design and maintain unit, functional, and integration tests that validate behavior across components and services.
• Improve throughput, latency, and scalability through performance testing, analysis, and tuning.
• Lead troubleshooting, root cause analysis, and resilience improvements in production while applying secure coding practices throughout the development lifecycle.

Work across teams

• Lead designs that span multiple services or domains and align teams on technical direction.
• Influence stakeholders through clear technical communication, strong design reviews, and well-reasoned recommendations.

Grow the team

• Mentor engineers through design guidance, code reviews, testing discipline, and hands-on coaching.
• Help the team improve software quality, security, performance, and operational excellence.

What we're looking for

• You lead through delivery. You have a track record of building and shipping meaningful capabilities in distributed systems at scale.
• You build for scale. You have hands-on experience with high-throughput, low-latency systems, ideally in streaming or real-time decisioning environments.
• You think in systems. You connect architecture, operations, and business outcomes and make pragmatic trade-offs.
• You influence through judgment and execution. You guide technical direction through strong judgment, clear communication, and credibility earned by doing the work.
• You are adaptable and hands-on. You are comfortable working across languages, tools, and changing priorities in small, fast-moving teams.
• You use AI tools well. AI coding tools are part of how you work, and you help others use them effectively.
• You communicate clearly. You write clear code, explain designs well, and work effectively with engineers, product partners, and senior stakeholders.
• You care about engineering quality. Testing, observability, security, and clean interfaces are core to how you build.
• You take ownership. You work well with ambiguity and take ownership when you notice opportunities or issues.

Technical domains

• 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.

Requirements

• Strong software development experience with ownership of complex systems, shared platforms, or critical technical domains.
• Hands-on experience designing and building distributed systems with high throughput and low latency.
• Strong fundamentals in software design, architecture, data structures, testing, code review, secure coding, performance, and troubleshooting.
• Experience building and operating cloud-native systems with strong observability and automation practices.
• Experience mentoring engineers and influencing technical direction across teams.
• Clear communicator who can work effectively with engineers, product partners, and senior stakeholders.
• Bachelor's degree in Computer Science, Software Engineering, or a related field — or equivalent experience.

To find US salary ranges, visit People Place. Under the Compensation tab, select "Salary Structures." Within the text of "Salary Structures," click on the link "salary structures 2025," through which you will be able to access the salary ranges for each Mastercard job family. For more information regarding US benefits, visit People Place and review the Benefits tab and the Time Off & Leave tab.