Founded in 1966, Mastercard is a worldwide transaction, payment-processing, and consulting company best known for its line of personal and business credit cards. As an employer, Ma
Director of AI Engineering
Location
Ireland
Posted
19 hours ago
Salary
0
Seniority
Senior
Job Description
Director of AI Engineering
Mastercard
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.
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Luxury PresenceDo it all with Luxury Presence. Build your brand, expand your network, & close more deals.
Luxury Presence is building the AI growth platform for real estate. Backed by Bessemer Venture Partners and other top investors, we're a Series C company that has hit $100M in annual recurring revenue. More than 90,000 real estate professionals, including over 30% of the WSJ Real Trends top 100 agents in the United States, use us to run and grow their business. The OpportunityWe don't just use AI. We build with it, ship with it, and think with it. We're in the top 1% of companies applying AI effectively, not just to our products, but to how we build them. With an unlimited budget for Anthropic tokens, our engineers use AI agents to write, review, and ship production code every day. We're building toward a world where humans design systems and AI builds them, and we're already further along that path than almost anyone else. As a Staff Software Engineer, you'll be a technical leader at the center of this transformation. 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