Manager, Software Engineering, AI Foundations

Mastercard•Atlanta, GA

1d•$140,000 - $231,000

About The Position

Mastercard is seeking a Manager, Software Engineering to lead the design, development, and delivery of AI platform capabilities that enable intelligent products and agentic experiences across B&MI. The role combines people leadership, technical ownership, and cross-functional delivery accountability. The manager will lead one or more engineering teams building reusable AI platform services, integration patterns, and production capabilities, while shaping architecture and ensuring solutions meet Mastercard standards for security, reliability, responsible AI, and governance. This hands-on engineering leader will scale teams, shape AI platform direction, and help product teams move AI solutions from experimentation into production. The role includes leading people and complex delivery, developing scalable and reusable AI platform services, guiding production integration of AI capabilities, defining architecture and engineering standards, and ensuring operational health. The manager will work with AI Engineers, Data Scientists, Product Managers, Architects, platform teams, leadership, and other partners. The position is based on the Atlanta, Georgia pay range. Mastercard intends to fill the position by 02/02/2027, or as soon as possible if that date has passed.

Requirements

Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
Proven experience leading software engineering teams delivering shared platforms, distributed systems, or AI-enabled capabilities.
Strong background in distributed systems, object-oriented programming, and backend engineering such as Java, Python, or similar.
Hands-on depth in software design and architecture, data structures, code review, and performance engineering.
Experience designing or integrating production AI capabilities, including LLM-based services, agentic systems, workflow orchestration, model APIs, or related platform patterns.
Demonstrated ability to drive architecture decisions and influence system design across teams.
Experience owning complex, cross-team initiatives end to end.
Strong understanding of operational practices, including observability, unit, functional, and integration testing, reliability, incident response, system performance, and secure software development.
Proven people management experience, including performance management, mentoring, and team development.

Nice To Haves

Experience building reusable platform capabilities used by multiple product or engineering teams.
Familiarity with AI evaluation, guardrails, responsible AI practices, and the challenges of operating AI-enabled systems in production.
Experience working in regulated environments with strong security, governance, risk, and compliance requirements.

Responsibilities

Lead, coach, and develop one or more software engineering teams by setting goals, managing performance, and creating development plans.
Build an engineering culture focused on ownership, quality, accountability, and continuous improvement; partner with leadership on hiring, team composition, and long-term planning.
Guide teams through change and ambiguity and connect team priorities to broader business and enterprise goals.
Own end-to-end delivery of complex initiatives across systems, services, or teams, including roadmaps, priorities, dependencies, risks, and cross-team blockers.
Establish planning, estimation, and tracking frameworks for predictable, high-quality delivery.
Lead development of scalable AI platform services and reusable capabilities for AI-powered products, intelligent workflows, and agentic systems.
Drive production integration of AI capabilities, including model inference, LLM-based services, orchestration, enterprise data and system connectivity, evaluation, and guardrails.
Promote shared engineering patterns and standardization to accelerate delivery and reduce duplication.
Define and evolve AI platform architecture in line with enterprise standards, and translate product, AI, and integration requirements into robust system designs.
Evaluate technologies and lead adoption decisions based on business value, technical fit, and long-term sustainability while balancing delivery, platform strategy, and technical debt.
Ensure systems meet reliability, security, compliance, performance, and observability standards; establish practices for AI evaluation, guardrails, lifecycle management, and production monitoring.
Own production health through troubleshooting, incident management, root cause analysis, and continuous improvement.
Drive adoption of code review, CI/CD, automated testing, and secure coding practices.
Collaborate with AI Engineers, Data Scientists, Product Managers, Architects, and platform teams to deliver integrated AI solutions.
Communicate technical strategy, risks, and progress clearly to leadership and partners.
Abide by Mastercard security policies, protect the confidentiality and integrity of accessed information, report suspected security violations or breaches, and complete required security training.

Benefits

Insurance, including medical, prescription drug, dental, vision, disability, and life insurance.
Flexible spending account and health savings account.
Paid leaves, including 16 weeks of new parent leave and up to 20 days of bereavement leave.
80 hours of Paid Sick and Safe Time.
25 days of vacation time and 5 personal days, prorated based on date of hire.
10 annual paid U.S. observed holidays.
401(k) with a company match.
Deferred compensation for eligible roles.
Fitness reimbursement or on-site fitness facilities.
Eligibility for tuition reimbursement.