Principal AI Platform Engineer - AI Center of Excellence

Principal AI Platform Engineer - AI Center of Excellence

Central role within Mastercard’s AI Center of Excellence. Lead design, build, and scale next‑generation infrastructure supporting Mastercard’s growing AI workloads, ensuring high‑performance, scalable platforms across compute, storage, networking, and accelerators.

The AI Center of Excellence is seeking a Principal AI Infrastructure Engineer to build and scale next‑generation infrastructure supporting Mastercard’s growing AI workloads. This role focuses on enabling high‑performance, scalable platforms across compute, storage, networking, and accelerators. The ideal candidate is technically deep, highly motivated, and brings an innovative, builder mindset to power advanced AI capabilities across the organization.

• Lead AI infrastructure roadmap for Mastercard’s on premise private cloud, spanning strategy, design, procurement, delivery, installation, and lifecycle management, in alignment with enterprise AI priorities and governance frameworks.
• Act as a product owner for AI infrastructure, translating business and data science needs into scalable, future proof platform capabilities that support both predictive ML and generative/agentic AI workloads at enterprise scale.
• Lead RFI and RFP processes for AI infrastructure components, including CPU, GPU, storage, and networking, defining technical and commercial evaluation criteria, reviewing vendor responses, and driving fact based selection decisions in partnership with sourcing and finance teams.
• Architect and scale infrastructure capable of training large scale predictive and generative models on petabytes of data, while supporting low latency inference (real time and batch) with thousands of transactions per second (TPS) across global workloads.
• Define and champion modern AI infrastructure standards, including high performance storage, high speed networking, and advanced data center requirements such as liquid cooling and power dense rack design.
• Partner closely with data science, MLOps, and platform teams to ensure infrastructure choices align with model development, training, deployment, observability, and responsible AI requirements across the AI lifecycle.
• Collaborate cross functionally with enterprise architecture, security, risk, governance, compliance, and legal teams to ensure solutions meet Mastercard’s regulatory, resiliency, and ethical AI standards.
• Influence senior leadership and executive stakeholders, clearly articulating trade offs, ROI, and risk, and confidently advocating for the right technical and architectural decisions through structured narratives and executive level presentations.
• Stay ahead of industry trends in AI infrastructure, Generative AI, and Agentic AI, continuously assessing emerging technologies and vendors to inform long term strategy and investment decisions.

• Bachelor’s degree in Computer Science, Electronics, or a related engineering field is required.
• Significant professional history of experience in large scale infrastructure, platform engineering, or systems architecture roles within a complex enterprise environment.
• Proven experience owning infrastructure roadmaps and driving delivery in on premise or private cloud environments at scale.
• Good working knowledge of AI/ML concepts, data science workflows, MLOps practices, and model lifecycle management.
• Familiarity with Generative AI and Agentic AI architectures, including their unique infrastructure, networking, and latency requirements.
• Deep understanding of compute (CPU/GPU), high performance storage, and networking technologies used in modern AI platforms.
• Hands on or architectural exposure to high density, high power AI infrastructure, including cooling, power, and data center design considerations.
• Strong product thinking—able to balance user needs, technical feasibility, cost, and long term platform evolution.
• Demonstrated experience running RFIs/RFPs, evaluating vendor proposals, and partnering with sourcing and finance teams to make informed investment decisions.
• Comfortable navigating and influencing within a large, matrixed organization, working effectively with security,…