Director, Software Engineering

Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Director, Software Engineering
Mastercard is a global technology company behind the world's fastest payments processing network. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making payment and data transactions safe, simple, smart, and accessible. Using secure data, resilient networks, strong partnerships, and deep expertise, our innovations help individuals, financial institutions, governments, and businesses realize their greatest potential.
Our Services offerings are experiencing rapid growth and this role within the AI Foundations - AIDE Engineering organization, are building the next generation of AI-driven fraud and risk solutions at global scale. We are seeking a Director of Engineering to lead and grow a high-impact AI/ML engineering organization responsible for delivering enterprise-grade AI capabilities across on-prem, cloud, and hybrid environments.
This is first and foremost a people leadership role.
The successful candidate will be a proven people manager who actively builds trust, develops talent, and creates an environment where engineers can do their best work. You will be accountable for attracting, coaching, retaining, and advancing senior technical talent, while setting clear expectations, providing regular feedback, and fostering a culture of ownership, inclusion, and continuous improvement.
At the same time, this leader must bring strong technical credibility. You will partner closely with Product Owners, Data Scientists, Enterprise Technology teams, and business stakeholders to translate strategy into execution. You will guide technical direction-not by coding day-to-day, but by asking the right questions, making sound trade-offs, and ensuring scalable, secure, and resilient solutions.
We are looking for a technical people leader who can:
Build, motivate, and lead cross-functional AI/ML and Data Engineering teams
Develop managers and senior ICs, preparing the organization to scale
Drive delivery of AI/ML, Graph Neural Network (GNN), and agentic solutions
Balance innovation with operational excellence and enterprise standards
You will lead and grow a diverse, high-impact team spanning AI, Data, Backend, and QA, collaborating closely across engineering and product teams to scale the platform and deliver measurable business outcomes.
Responsibilities
Direct the vision, strategy, and execution of modern, architecture-driven deployments for AI/Machine Learning solutions and products across Mastercard's ecosystem.
Provide leadership and guidance in high-level technical discussions, influencing engineering teams and cross-functional partners to shape scalable, secure, and high-quality architectures for AI/ML model deployment and serving.
Establish enterprise deployment frameworks, reference architectures, and standards that ensure AI/ML models are production-ready, resilient, and scalable across global markets.
Oversee the development scalable AI/ML, GNN, Agentic AI products, defining long-term technical roadmaps and ensuring alignment with business priorities and market needs.
Drive governance and best practices for AI/ML operationalization, including performance, observability, compliance, and lifecycle management.
Build, motivate, and lead cross-functional AI/ML and Data Engineering teams
Develop managers and senior ICs, preparing the organization to scale
Balance innovation with operational excellence and enterprise standards
Experiences
Proven technology leadership delivering enterprise-grade AI/ML and data engineering platforms at scale-taking solutions from prototype to production with strong engineering discipline.
Deep architectural expertise in AI/ML platforms, including model lifecycle governance, Responsible AI controls, and operational readiness (observability, reproducibility, auditability).
Demonstrated experience leading Graph ML / GNN initiatives end-to-end, including graph data/feature pipelines, performance optimization, and production integration patterns.
Strong understanding of agentic system architectures (single/multi-agent patterns, tool-calling, retrieval/grounding, guardrails) and what it takes to deploy agents safely in regulated enterprise environments.
Expertise designing and guiding teams building high-throughput distributed systems (concurrency, parallelism, event-driven patterns) that support real-time/near-real-time AI decisioning workloads.
Track record driving data engineering excellence: scalable ingestion and transformation pipelines, feature extraction/engineering, data quality automation, lineage, and cost-efficient processing.
Hands-on familiarity with cloud-native and hybrid/on-prem deployment patterns for AI workloads.
Excellent communication and executive stakeholder leadership-able to align Product, Data Science, Platform, and Engineering teams, clarify ownership boundaries, and drive crisp technical decisions.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard's security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.