Principal AI Engineer

Reposted 3 Hours Ago
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Dublin, IRL
Hybrid
Senior level
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
We are a global technology company in the payments industry.
The Role
The Principal AI Engineer will architect and scale AI systems, lead technical strategies, and mentor engineers while collaborating with diverse teams to support business needs.
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
Principal AI Engineer
Overview
We are seeking a highly accomplished Principal AI Engineer to define and drive the technical direction of our AI platforms and solutions. This role is focused on architecting, building, and scaling production-grade AI systems that deliver durable business impact. As a senior technical authority, you will lead through deep hands-on expertise, influence technical strategy across teams, and raise the engineering bar for AI development across the organization.
The ideal candidate combines exceptional engineering depth with strong system design skills, applied research experience, and the ability to guide complex AI initiatives from conception through global-scale production
Role
As a Principal AI Engineer, you will be responsible for designing, implementing, and operating advanced AI systems that support critical business and client needs in a scalable, secure, and reliable manner. You will partner closely with product, engineering, and data leaders to translate business intent into robust AI architectures and platforms.
This role prioritizes technical leadership over people management, with impact achieved through architecture ownership, technical decision-making, and mentorship of senior engineers and data scientists.
All about you:
Demonstrated experience designing and building AI/ML systems in production at scale, ideally across multiple problem domains
Expert-level proficiency in Python and deep experience with modern AI frameworks such as PyTorch and TensorFlow
Strong experience with cloud-native architectures and AI infrastructure on platforms such as AWS, Azure, or GCP
Deep understanding of machine learning, deep learning, NLP, generative AI, and transformer-based architectures (e.g., BERT, GPT-style models, ViTs)
Proven expertise in MLOps, including model versioning, deployment strategies, monitoring, evaluation, and lifecycle management
Strong systems-thinking mindset, with experience designing resilient, scalable, and cost-efficient AI services
Experience working with large-scale data architectures, streaming and batch processing, and model inference optimization
Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
Track record of technical mentorship and influence without relying on formal line management
Comfortable operating in high-ambiguity environments and making sound technical judgments with incomplete information
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

  • Expert-level proficiency in Python
  • Experience designing and building AI/ML systems in production at scale
  • Deep experience with modern AI frameworks such as PyTorch and TensorFlow
  • Strong experience with cloud-native architectures and AI infrastructure on AWS, Azure, or GCP
  • Proven expertise in MLOps including model versioning and deployment strategies

What the Team is Saying

Jenny
Mastercard

Mastercard Compensation & Benefits Highlights

  • Retirement Support Company information highlights a 10% retirement match on U.S. roles, positioned as best‑in‑class and well above typical large‑employer benchmarks. This level of employer contribution materially strengthens long‑term savings.
  • Leave & Time Off Breadth U.S. postings list 25 vacation days, 5 personal days, 10 company holidays, 80 hours of paid sick/safe time, and up to 20 days of bereavement. A minimum of 16 weeks paid new‑parent leave (including adoption and foster) further expands paid time away.
  • Parental & Family Support Benefits include a minimum of 16 weeks paid new‑parent leave and family‑building support such as fertility, adoption, and surrogacy where legally available. Dependent scholarships, counseling, and protection benefits contribute additional family support.

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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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About our Teams

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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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