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 of AI Engineering
Overview
Mastercard is seeking a Director of AI Engineering to lead a specialised team of AI engineers focused on foundation model development and the delivery of high‑value AI use cases. This role is responsible for driving the practical application of transformer‑based and generative AI capabilities—ensuring models are effectively developed, adapted, and deployed to solve real business problems.
You will lead a team working at the intersection of model development and use case execution, translating foundational AI capabilities into scalable, production‑ready solutions. The role requires strong technical judgement, delivery leadership, and the ability to balance innovation with enterprise requirements for reliability, security, and governance.
Role
In this role, you will lead a team responsible for developing and applying foundation model capabilities to priority use cases.
Key responsibilities include:
Lead a team of AI engineers focused on foundation model development, fine‑tuning, and optimisation, particularly transformer‑based and generative AI systems
Drive the end‑to‑end delivery of AI use cases, from problem definition through model integration and production deployment
Partner with product and business stakeholders to identify and prioritise high‑impact AI use cases, translating them into clear technical execution plans
Ensure effective use of foundation models across use cases, including prompting strategies, embeddings, fine‑tuning, evaluation, and performance optimisation
Collaborate with data engineering and platform teams to ensure data readiness, model integration, and scalable deployment patterns
Establish best practices for model evaluation, experimentation, and continuous improvement, ensuring solutions are robust and measurable
Embed responsible AI practices, including model validation, bias considerations, and appropriate guardrails
Provide technical guidance and coaching to engineers, ensuring high standards in both AI development and software engineering practices
Track delivery progress, manage risks, and ensure timely, high‑quality execution of use cases aligned to program priorities
All About You
Proven experience leading teams delivering AI/ML solutions in production, particularly in use‑case driven environments
Strong hands‑on understanding of transformer architectures and generative AI, including fine‑tuning, prompting, embeddings, and evaluation
Experience bridging model development and real‑world application, translating AI capabilities into business impact
Solid engineering background, with familiarity in Python, ML frameworks (e.g. PyTorch/TensorFlow), and production deployment patterns
Experience working with data engineering and MLOps practices to support training, evaluation, and inference at scale
Strong stakeholder management skills, with the ability to align technical delivery to business priorities and measurable outcomes
Demonstrated ability to lead and develop high‑performing teams, providing technical direction, coaching, and delivery oversight
Comfortable operating in a fast‑moving, evolving AI landscape with ambiguity and shifting priorities
Excellent communication skills, able to articulate complex AI concepts to both technical and non‑technical audiences
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.
