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Senior Principal AI Engineer- AI Center of Excellence

Finicity, a Mastercard Company831 open roles

Where
San Francisco California
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Your applicationOpen nowSenior Principal AI Engineer- AI Center of ExcellenceFinicity, a Mastercard Company · San Francisco California
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The clock on this job

Early applications get read.

8.1% of postings close within 7 days. Measured by our own scanner across the market. Finicity, a Mastercard Company postings stay open a median of 30 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.6%3 days
  3. 8.1%7 days
  4. 15.0%14 days
  5. 33.9%30 days
This job: posted today

Finicity, a Mastercard Company median: 30 days open

The posting

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

Senior Principal AI Engineer- AI Center of Excellence

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. 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.

Overview:

The AI Center of Excellence is seeking a Senior Principal AI Engineer – AI Infrastructure to serve as a technical expert and thought leader for Mastercard’s enterprise AI infrastructure. This senior individual-contributor role will shape the architecture and engineering of secure, scalable, production-grade platforms supporting LLM model training and inferencing, machine learning models, large language models (LLMs), agentic AI, and emerging AI capabilities in production. The successful candidate will bring deep expertise in high-performance computing (HPC), GPU and accelerated computing, rack-scale systems architecture, private and hybrid cloud, Kubernetes, high-performance networking and storage, observability, security, and reliability. They will work closely with AI Engineers, Data Scientists, Platform Engineers, Security, Architecture, and Product partners to deliver resilient, cloud-native AI platforms in a highly regulated environment.

About the Role: • Define the technical vision, architecture, and engineering standards for enterprise AI infrastructure and platforms. • Lead the architecture and evolution of HPC, GPU and accelerated compute, rack-scale systems, private and hybrid cloud, Kubernetes, high-performance networking, storage, and AI platform services. • Design infrastructure supporting LLM training and inferencing, model serving, machine learning workloads, agentic AI orchestration, and emerging AI capabilities. • Solve complex infrastructure, performance, and scalability challenges through hands-on architecture, prototyping, performance engineering, and troubleshooting. • Establish engineering patterns for reliability, resiliency, observability, automation, capacity management, security, and operational readiness. • Embed security, privacy, Responsible AI, governance, compliance, and auditability into AI infrastructure by design. • Evaluate emerging AI, HPC, GPU, networking, storage, and infrastructure technologies and influence enterprise architecture and platform roadmaps. • Lead complex cross-functional technical initiatives and mentor engineers through architecture reviews, engineering standards, reference designs, and knowledge sharing.

All About You: • Years of experience in AI engineering, high-performance computing, platform engineering, infrastructure engineering, distributed systems, cloud technology, or related disciplines. • Proven experience architecting and operating secure, mission-critical platforms at enterprise scale. • Deep expertise in HPC, GPU/accelerated computing, rack-scale systems architecture, Kubernetes, private and hybrid cloud, high-speed networking, storage, and infrastructure automation. • Experience supporting LLM training and inferencing, machine learning models, large language models, agentic AI, and production AI platforms. • Strong knowledge of distributed systems, SRE, observability, resiliency, security, governance, compliance, and production operations. • Demonstrated ability to lead complex architecture and engineering initiatives through technical expertise, influence, and cross-functional collaboration. • Strong communication and mentoring skills with the ability to engage senior stakeholders and elevate technical expertise across engineering teams. • Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related discipline; advanced degree preferred.

#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 [email protected] 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.

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.

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.THIS POSTING IS NOT FOR A CURRENT VACANCY, BUT MASTERCARD IS SEEKING RESUMES TO REVIEW IN THE FUTURE WHEN JOBS BECOME AVAILABLE.

Pay Ranges

San Francisco, California: $254,000 - $407,000 USD

Atlanta, Georgia: $212,000 - $339,000 USD

Boston, Massachusetts: $244,000 - $390,000 USD

Miami, Florida: $212,000 - $339,000 USD

New York City, New York: $254,000 - $407,000 USD

O'Fallon, Missouri: $212,000 - $339,000 USD

Purchase, New York: $244,000 - $390,000 USD

Remote - New York: $212,000 - $339,000 USD

Seattle, Washington: $244,000 - $390,000 USD

Job Posting Window

Posting windows may change based on the volume of applications received and business necessity. Candidates are encouraged to apply expeditiously.

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