Jobs / United States / Mastercard International Incorporated
Senior Principal AI Engineer- AI Center of Excellence
Mastercard International Incorporated · 🇺🇸 9 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 76 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 286 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Mastercard International Incorporated paid sponsored hires in similar roles10 certified filings for “Senior Software Engineer” (Software Developers) in MO: $115k–$138k, median $127k. Most were filed at wage level II (50%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Mastercard International Incorporated
The US Department of Labor certified 76 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 286 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Mastercard International Incorporated →
About the role
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