Senior Principal AI Engineer- AI Center of Excellence
$254k - $407k • San Francisco, California • Full-time
Posted 4d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Infrastructure Engineer
About the job
The AI Center of Excellence is seeking a Senior Principal AI Engineer to serve as a technical expert and thought leader for Mastercard’s enterprise AI infrastructure. This 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.
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.
Requirements
- 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.