Senior Principal AI Engineer- AI Center of Excellence

Mastercard; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Mastercard seeks a Senior Principal AI Engineer to lead AI infrastructure, shaping scalable, secure platforms for training and inference of LLMs and AI workloads. You will drive HPC, GPU, Kubernetes, and private/hybrid cloud initiatives across the enterprise, partnering with security, architecture, and product teams.

You will mentor engineers, set reliability standards, and ensure governance and auditability are built in from design through operations, in a highly regulated environment.

Qualifications

• 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.

Responsibilities

• 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.

Skills

HPC

GPU computing

Kubernetes

Distributed systems

Observability

Security

Mentoring

Cross-functional collaboration

Education

Bachelors in CS/Engineering

Advanced degree preferred

Tools

Linux

GPU clusters

Observability tooling

Security tooling

Job description

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 [e-mail] and identify the type of accommodation or assistance you are requesting.