Director of AI Engineering

Reposted 21 Hours Ago
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Malahide, Dublin, IRL
Hybrid
Expert/Leader
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
We are a global technology company in the payments industry.
The Role
Lead an AI engineering team to develop, fine-tune, and deploy foundation models and generative AI for high-impact use cases. Drive end-to-end delivery, collaborate with product, data engineering and platform teams, embed responsible AI practices, and provide technical guidance to ensure scalable, production-ready solutions.
Summary Generated by Built In
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.

Skills Required

  • Proven experience leading teams delivering AI/ML solutions in production
  • Strong hands-on understanding of transformer architectures and generative AI (fine-tuning, prompting, embeddings, evaluation)
  • Solid engineering background with familiarity in Python and ML frameworks (PyTorch/TensorFlow)
  • Experience with production deployment patterns and MLOps to support training, evaluation, and inference at scale
  • Experience partnering with product and business stakeholders to translate AI capabilities into business impact
  • Demonstrated ability to lead and develop high-performing teams, providing technical direction and coaching
  • Embed responsible AI practices including model validation, bias considerations, and guardrails
  • Excellent communication skills to articulate complex AI concepts to technical and non-technical audiences

What the Team is Saying

Jenny
Mastercard

Mastercard Compensation & Benefits Highlights

  • Retirement Support A 10% company retirement match (401k or equivalent) is explicitly highlighted in company materials. This level of employer contribution stands out as a core strength of the package.
  • Leave & Time Off Breadth A global minimum of 16 weeks fully paid new‑parent leave and generous U.S. PTO (vacation, personal days, holidays, sick time, and bereavement) are clearly spelled out. These provisions indicate broad time‑off coverage across life events.
  • Wellbeing & Lifestyle Benefits Hybrid work, a four‑week “work from elsewhere” option, meeting‑free well‑being days, five paid volunteer days, mental‑health resources, and fitness reimbursement/on‑site gyms are emphasized. Together they reflect a holistic approach to flexibility and wellbeing.

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The Company
HQ: Purchase, NY
38,800 Employees
Year Founded: 1966

What We Do

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a resilient 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.

Why Work With Us

We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.

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Hybrid Workspace

Employees engage in a combination of remote and on-site work.

In our ongoing workplace evolution, we’ve introduced hybrid work, Work-From-Elsewhere Weeks and Meeting-Free Days.

Typical time on-site: 3 days a week
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