Vice President, Software Engineering - Dmp

Mastercard Mastercard · Fintech · O Fallon, MO +1 · Engineering

Mastercard is seeking a Vice President of Software Engineering to lead the Authorization Decisioning domain within the Decision Management program. This role will define and drive the engineering vision and strategy, lead the delivery of complex initiatives including AI/ML inference and data pipelines, and ensure platform reliability, performance, scalability, security, and compliance in a regulated, mission-critical environment. The role requires strong leadership in building and scaling high-performing teams and ensuring operational excellence.

What you'd actually do

  1. Define and drive the engineering vision and strategy for Authorization and Authentication Decisioning.
  2. Lead the delivery of complex, cross-functional initiatives spanning real-time decisioning, rules engines, AI/ML inference, data pipelines, and platform services.
  3. Establish and scale engineering best practices, standards, and frameworks across teams.
  4. Ensure platform reliability, performance, scalability, security, and compliance in line with the demands of global, mission-critical systems.
  5. Own operational excellence, including SLAs, observability, and incident management.

Skills

Required

  • Director or Vice President of Software Engineering, Architecture, or comparable senior leadership role
  • Leading distributed, global engineering organizations
  • Modern application architectures (APIs, microservices, event-driven, batch processing, data platforms)
  • Java
  • REST APIs
  • Kafka
  • Messaging systems (MQ)
  • Spring
  • CI/CD pipelines (e.g., Jenkins)
  • Cloud platforms (e.g., Pivotal Cloud Foundry or similar)
  • High-scale, low-latency, highly available platforms
  • Regulated or mission-critical environments
  • Large, complex programs with predictable, on-time, and on-budget delivery
  • SDLC methodologies (Scrum, Kanban, SAFe)
  • Resilient systems (security, reliability, testing, observability, service-oriented design)
  • Communication and storytelling
  • Influencing executive, business, and technical stakeholders
  • Analytical thinking
  • Decision-making in ambiguous and complex environments
  • Bachelor’s degree in Engineering, Computer Science, Mathematics, or related quantitative field, or equivalent practical experience

What the JD emphasized

  • AI/ML inference
  • low latency
  • regulated
  • mission-critical