Mastercard
Arlington, Virginia
+ 8 other locations
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.
Principal AI Platform Engineer - AI Center of Excellence
Who is Mastercard?
Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.
Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Overview:
The AI Center of Excellence is seeking a Principal AI Infrastructure Engineer to build and scale next-generation infrastructure supporting Mastercard’s growing AI workloads. This role focuses on enabling high-performance, scalable platforms across compute, storage, networking, and accelerators. The ideal candidate is technically deep, highly motivated, and brings an innovative, builder mindset to power advanced AI capabilities across the organization.
About the Role:
• Lead AI infrastructure roadmap for Mastercard’s on premise private cloud, spanning strategy, design, procurement, delivery, installation, and lifecycle management, in alignment with enterprise AI priorities and governance frameworks.
• Act as a product owner for AI infrastructure, translating business and data science needs into scalable, future proof platform capabilities that support both predictive ML and generative/agentic AI workloads at enterprise scale.
• Lead RFI and RFP processes for AI infrastructure components, including CPU, GPU, storage, and networking, defining technical and commercial evaluation criteria, reviewing vendor responses, and driving fact based selection decisions in partnership with sourcing and finance teams.
• Architect and scale infrastructure capable of training large scale predictive and generative models on petabytes of data, while supporting low latency inference (real time and batch) with thousands of transactions per second (TPS) across global workloads.
• Define and champion modern AI infrastructure standards, including high performance storage , high speed networking , and advanced data center requirements such as liquid cooling and power dense rack design.
• Partner closely with data science, MLOps, and platform teams to ensure infrastructure choices align with model development, training, deployment, observability, and responsible AI requirements across the AI lifecycle.
• Collaborate cross functionally with enterprise architecture, security, risk, governance, compliance, and legal teams to ensure solutions meet Mastercard’s regulatory, resiliency, and ethical AI standards.
• Influence senior leadership and executive stakeholders, clearly articulating trade offs, ROI, and risk, and confidently advocating for the right technical and architectural decisions through structured narratives and executive level presentations.
• Stay ahead of industry trends in AI infrastructure, Generative AI, and Agentic AI, continuously assessing emerging technologies and vendors to inform long term strategy and investment decisions.
All About You:
• Bachelor’s degree in Computer Science, Electronics, or a related engineering field is required.
• Significant professional history of experience in large scale infrastructure, platform engineering, or systems architecture roles within a complex enterprise environment.
• Proven experience owning infrastructure roadmaps and driving delivery in on premise or private cloud environments at scale.
• Good working knowledge of AI/ML concepts, data science workflows, MLOps practices, and model lifecycle management.
• Familiarity with Generative AI and Agentic AI architectures, including their unique infrastructure, networking, and latency requirements.
• Deep understanding of compute (CPU/GPU), high performance storage, and networking technologies used in modern AI platforms.
• Hands on or architectural exposure to high density, high power AI infrastructure, including cooling, power, and data center design considerations.
• Strong product thinking—able to balance user needs, technical feasibility, cost, and long term platform evolution.
• Demonstrated experience running RFIs/RFPs, evaluating vendor proposals, and partnering with sourcing and finance teams to make informed investment decisions.
• Comfortable navigating and influencing within a large, matrixed organization, working effectively with security, governance, architecture, and compliance stakeholders.
• Executive ready communicator with the ability to present complex technical topics clearly, persuasively, and credibly to senior leaders.
• Strategic, opinionated, and data driven, with the confidence to challenge assumptions and defend well reasoned design decisions.
• Curious, forward looking, and passionate about building the AI foundations that enable enterprise scale innovation.
#AI1
Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
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:
In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.
Arlington, Virginia: $195,000 - $323,000 USD
Atlanta, Georgia: $170,000 - $281,000 USD
Austin, Texas: $170,000 - $281,000 USD
Boston, Massachusetts: $196,000 - $323,000 USD
Miami, Florida: $170,000 - $281,000 USD
New York City, New York: $204,000 - $337,000 USD
O'Fallon, Missouri: $170,000 - $281,000 USD
Purchase, New York: $196,000 - $323,000 USD
San Francisco, California: $204,000 - $337,000 USD