Director, Software Engineering

About Mastercard

Mastercard is a global leader in technology-driven payments, operating in over 210 countries and territories. Our mission is to foster an inclusive digital economy by enabling secure, straightforward, and intelligent transactions. We combine innovation, technology, and partnerships to provide products and services that unlock potential for individuals, financial institutions, governments, and businesses worldwide.

Role Overview

We are seeking a Director of Software Engineering to lead the development and delivery of applied AI and agentic capabilities within the CNPF Data & AI organization. This position involves hands-on leadership in building the Mastercard Virtual C-Suite product line. The role focuses on advancing next-generation agent-driven applications, reusable agent frameworks, and scalable AI platforms that act as intelligent personas, embedded features, and orchestrated digital workers addressing key enterprise and customer challenges.

Key Responsibilities

• Define and drive the engineering vision for agentic applications, frameworks, and reusable AI capabilities across diverse products and teams.
• Build and grow engineering teams developing agents as integrated product features, personas for specific workflows, and orchestration layers enabling complex reasoning and action execution.
• Lead the architecture and production deployment of agentic systems covering context management, memory, tool integration, workflow orchestration, monitoring, evaluation, and safety mechanisms.
• Develop a unified engineering framework standardizing design, testing, deployment, monitoring, and iterative improvement of intelligent agents at enterprise scale.
• Collaborate closely with Product, Data Science, Security, Risk, and Platform groups to transform high-impact use cases into scalable software solutions.
• Champion adoption of AI-assisted engineering tools and developer productivity enhancements to accelerate experimentation, quality, and delivery.
• Shape platform capabilities for managing agent lifecycles, prompt handling, model access, retrieval mechanisms, policy enforcement, telemetry, and feedback integration.
• Drive excellence in software architecture, coding standards, testing practices, release management, reliability, incident response, and cost-efficient operations within AI-native systems.
• Establish clear, quantifiable success metrics for agentic products and platforms, including adoption rates, accuracy, latency, resilience, developer experience, and business impact.
• Create reusable architectural patterns and reference implementations facilitating faster movement from experimentation to governed, production-grade delivery.
• Represent engineering leadership in executive and cross-functional forums, effectively communicating technical trade-offs, delivery status, risks, and strategic opportunities.

Qualifications

• Proven leadership experience managing software engineering teams including managers and cross-functional groups within product, platform, or enterprise technology contexts.
• Strong record of designing and scaling secure, resilient distributed systems and cloud-native platforms servicing multiple teams or business units.
• Direct experience developing or scaling Generative AI, large language model (LLM)-powered applications, AI agents, workflow automation, or similar intelligent software technologies.
• Deep expertise in agentic engineering concepts such as tool invocation, orchestration, planning, memory and context management, retrieval, evaluation, observability, and human feedback control loops.
• Skilled in creating reusable engineering frameworks or internal platform services that expedite broad enterprise adoption of advanced technologies.
• Solid foundation in modern application architectures, including APIs, microservices, event-driven systems, and deployment on cloud platforms such as AWS, Azure, or Kubernetes.
• Ability to balance rapid innovation with necessary governance demands including security, privacy, reliability, risk mitigation, and responsible AI practices.
• Experience promoting AI development tools and engineering productivity improvements to enhance developer outcomes and software delivery.
• Exceptional communication and stakeholder management skills, capable of articulating complex technical decisions clearly to executives and partners.
• Bachelor’s degree in Computer Science, Software Engineering, or related discipline required; advanced degrees preferred.

About You

The ideal candidate combines technical expertise and organizational leadership to link strategic vision with hands-on engineering execution. You are motivated by establishing foundational platforms for agentic software and transforming AI capabilities into secure, scalable, practical products. You appreciate that intelligent agents can serve as assistants, personas, workflow contributors, and product capabilities requiring effective governance, measurement, and refinement. You have a strong action orientation, sound engineering judgment, and a track record of building high-performing teams that deliver quickly without compromising quality or trust. You excel at defining long-term platform strategy, guiding architecture and delivery, and facilitating AI adoption through robust tooling and reusable patterns.

Corporate Security Responsibilities

• Comply with Mastercard’s security policies and procedures.
• Maintain confidentiality and integrity of accessed information.
• Report any suspected security breaches or violations.
• Complete all mandatory security training within prescribed timelines.