Lead AI Infrastructure Architect - Private Cloud & GenAI

Mastercard; Boston (MA); On-site; USD 196,000 - 323,000; Full time

Benefits offered by this job

Insurance benefits

401k with company match

Paid time off

Tuition reimbursement

Job summary

Mastercard is seeking a Principal AI Platform Engineer to lead the AI infrastructure roadmap for our on-premise private cloud, aligning with enterprise AI priorities and governance. You will act as product owner, translate data science needs into scalable platform capabilities, and drive RFIs/RFPs with vendors.

You will architect and scale infrastructure to train large models and support low-latency inference across global workloads, while collaborating with data science, MLOps, and security

Qualifications

• Experience with large-scale infrastructure and platform engineering in a complex enterprise.
• Experience owning infrastructure roadmaps and delivering in on-prem/private clouds.
• Knowledge of AI/ML concepts, data science workflows, MLOps, and model lifecycle.
• Familiarity with Generative AI and Agentic AI architectures and their infra requirements.
• Strong product thinking balancing user needs, feasibility, cost, and evolution.

Responsibilities

• Lead AI infrastructure roadmap for on-premise private cloud.
• Act as product owner for AI infrastructure translating needs into scalable platform capabilities.
• Lead RFIs/RFPs for AI infra components.
• Architect and scale infra for training large-scale models with low-latency inference.
• Collaborate with data science, MLOps, and platform teams for alignment.
• Partner with security and governance to meet regulatory standards.
• Stay ahead of AI infra trends and evaluate emerging tech.

Skills

AI infrastructure

RFIs/RFPs

Executive communication

On-prem/private cloud

Vendor evaluation

Education

Bachelor's degree in Computer Science, Electronics, or related engineering field

Job description

Mastercard is seeking a Principal AI Platform Engineer to lead the AI infrastructure roadmap for our on-premise private cloud, aligning with enterprise AI priorities and governance. You will act as product owner, translate data science needs into scalable platform capabilities, and drive RFIs/RFPs with vendors.

You will architect and scale infrastructure to train large models and support low-latency inference across global workloads, while collaborating with data science, MLOps, and security