AI Infra Architect — Enterprise LLM, HPC & Kubernetes

Mastercard; New York (NY); On-site; USD 212,000 - 407,000; Full time

Benefits offered by this job

Medical insurance

Flexible spending account

Paid parental leave (16 weeks)

Bereavement leave

Paid Sick Time

Vacation 25 days

Personal days 5

Holidays 10

401k with match

Deferred compensation

Fitness reimbursement

Tuition reimbursement

Job summary

Mastercard is building secure, scalable, production-grade enterprise AI. This role helps set the technical direction for AI infrastructure across LLMs, model serving, and agentic AI in a regulated environment.

The onsite New York position focuses on architecture standards, reliability, observability, and enterprise-scale operations. You will lead HPC and Kubernetes implementations, guide private/hybrid cloud adoption, and mentor engineers through architecture reviews and roadmaps.

Qualifications

• Bachelor’s degree in CS, Engineering, IS, Data Science, or related field.
• Experience architecting secure, mission-critical platforms at scale.
• Deep expertise in HPC, GPU, rack-scale systems, Kubernetes, cloud environments.

Responsibilities

• Define the technical vision, architecture, and engineering standards for enterprise AI infrastructure.
• Lead architecture of HPC, GPU, rack-scale systems, and private/hybrid cloud environments.
• Own platform capabilities across Kubernetes, high-performance networking, storage, and AI services.
• Design infrastructure for LLM training/inferencing, model serving, ML workloads, and agentic AI orchestration.
• Resolve complex infra, performance, and scalability challenges via hands-on architecture and prototyping.
• Establish engineering patterns for reliability, observability, automation, security, and capacity management.
• Embed security, privacy, Responsible AI, governance, and auditability by design.
• Evaluate emerging AI/HPC/Networking/storage tech and influence roadmaps.
• Lead cross-functional initiatives and mentor engineers through architecture reviews and designs.

Skills

AI engineering

HPC

Platform engineering

Distributed systems

Kubernetes

Cloud infrastructure

Security & compliance

Observability

Mentoring

Leadership

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or related discipline

Advanced degree preferred

Job description

Mastercard is building secure, scalable, production-grade enterprise AI. This role helps set the technical direction for AI infrastructure across LLMs, model serving, and agentic AI in a regulated environment.

The onsite New York position focuses on architecture standards, reliability, observability, and enterprise-scale operations. You will lead HPC and Kubernetes implementations, guide private/hybrid cloud adoption, and mentor engineers through architecture reviews and roadmaps.