Jobs at Mastercard

The Lead Security Engineer advocates secure design practices within Mastercard, leading complex security initiatives, providing expert guidance, and ensuring compliance with security policies and standards.

The Lead Cryptographic Security Engineer is responsible for guiding secure cryptographic implementations, advising teams, and enhancing security posture through governance of key management standards.

As the Lead Program Security Engineer, you'll ensure security within Mastercard's Data and AI initiatives by implementing secure practices, architecture, and risk management across teams and products.

Lead technical program manager for Mastercard Fraud Products responsible for planning and delivering medium-to-large technical programs on a Java-based decisioning platform. Manage SAFe/Agile delivery, coordinate cross-functional teams, communicate status to stakeholders, handle PCI and audit controls, assess development impacts, and drive solutions to reduce fraud while meeting scope, schedule, cost and quality objectives.

Lead technical program management for Mastercard's Decision Management fraud platform. Plan, execute, and communicate medium-to-large Agile projects, manage cross-team delivery, assess technical impacts, document audit/PCI controls, and partner with business, architects, and engineers to deliver high-performance fraud and identity solutions.

Lead and deliver production-grade agentic AI systems and platforms. Define engineering vision, build and scale teams, architect agent frameworks and orchestration, ensure security, observability, and governance, partner with Product and Data Science, and drive adoption of AI tooling and developer productivity across the organization.

Lead engineering for agentic AI products and platforms: define vision, build scalable agent frameworks, deliver production-grade LLM-powered systems, drive AI tooling adoption, ensure security/governance, and partner cross-functionally to operationalize agentic capabilities.

Lead and deliver medium-to-large fraud and identity projects for Mastercards Decision Management Platform. Plan, prioritize, and manage SAFe Agile delivery, coordinate stakeholders, mitigate risks, ensure PCI/audit controls, provide technical guidance, and drive cross-program initiatives to meet scope, schedule, quality, and business objectives.

Lead technical program manager for Mastercard's Decision Management Platform: plan, execute, and communicate medium-to-large fraud projects; manage SAFe Agile delivery; coordinate engineers, analysts, and stakeholders; ensure scope, schedule, quality, PCI compliance, and positive business value; mitigate risks and support cross-program initiatives.

Lead and deliver medium-to-large technical programs for Mastercard's fraud Decision Management Platform. Plan, prioritize, and execute projects in SAFe/Agile, coordinate cross-functional teams, manage stakeholders, ensure PCI/audit controls, provide technical support to business owners, and drive data-driven continuous improvement.

Lead and deliver medium-to-large technical fraud programs for Mastercard's Java-based Decision Management Platform. Plan, execute, and communicate project scope, schedule, cost, and quality; manage SAFe/Agile delivery; coordinate stakeholders, audit/PCI controls, and technical impacts; mentor teams and drive cross-program improvements.

Lead and deliver medium-to-large technical fraud and identity projects for Mastercard's Decision Management Platform. Plan, prioritize, and manage SAFe/Agile delivery, coordinate stakeholders, document PCI and audit controls, mitigate risks, and provide technical support to ensure on-time, on-scope delivery while driving cross-team collaboration and continuous improvement.

Lead engineering for agentic AI products and platforms: build and scale teams, define architecture and frameworks for LLM-driven agents, ensure production-grade reliability, observability, security, and cross-functional adoption of AI tooling and governance.

Lead engineering strategy and hands-on delivery for agentic, LLM-powered systems and reusable AI platforms. Build and scale teams and frameworks for orchestration, retrieval, observability, safety, and production-grade deployment; partner with Product, Data Science, Security, and Platform teams to move agentic solutions from experimentation to governed, scalable production.

Lead and scale engineering teams to design, build, and productionize agentic AI systems and reusable platform capabilities. Define architecture, frameworks, observability, safety guardrails, and developer tooling to move LLM/agent solutions from experimentation to secure, scalable enterprise production while partnering with product, data science, security, and platform teams.

Lead engineering for production-grade agentic AI products and reusable agent frameworks. Drive architecture, platform capabilities (lifecycle, retrieval, observability, safety), team scaling, AI tooling adoption, and cross-functional delivery to turn experiments into secure, scalable enterprise solutions.

Lead Technical Program Manager responsible for planning and executing medium-to-large fraud technology projects on Mastercard's Java-based Decision Management Platform. Manage SAFe/Agile delivery, coordinate cross-functional teams, ensure scope/cost/schedule/quality, document PCI/audit controls, support business owners, and drive data-driven continuous improvement and stakeholder communication.

Lead engineering strategy and delivery for agentic AI products and platforms. Build and scale teams, drive architecture for production-grade agent systems, establish reusable frameworks, partner cross-functionally, and ensure security, observability, and governed AI adoption.

Lead engineering strategy and hands-on delivery for agentic AI products and reusable agent frameworks. Build and scale teams and cloud-native platforms, drive architecture for production-grade agent systems (memory, orchestration, tool integration, observability, safety), partner cross-functionally, establish engineering frameworks, and measure adoption, quality, and business impact.

Lead engineering strategy and hands-on delivery for agentic AI products and platforms. Build and scale teams and reusable agent frameworks, drive architecture for production-grade LLM/agent systems (context, memory, tool integration, orchestration, observability, safety), partner with Product and Data Science, and establish engineering standards, tooling, and measurable success criteria to move experiments into governed, scalable production.