Jobs / United States / Mastercard International Incorporated
Lead Agentic AI Designer
Mastercard International Incorporated · 🇺🇸 Purchase, New York
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.
- 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).
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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 Lead Agentic AI Designer Overview Mastercard Services’ Operational Intelligence (OI) team is expanding its AI platform with agentic AI and large language model (LLM)–driven autonomous systems. This role focuses on designing, building, and scaling enterprise-grade, multi-agent AI platforms that power critical operational workflows. This position begins as a hands-on individual contributor with end-to-end ownership of architecture and delivery. Following a successful initial launch, the role is expected to evolve to include people leadership responsibilities. The Lead AI Engineer, Agentic AI serves as a senior technical contributor, driving architecture, implementation, and production readiness while partnering closely with Product and mentoring other engineers. They will design and deploy large-scale LLM applications and autonomous agent systems integrated with Mastercard’s enterprise platforms. This role emphasizes production-quality engineering, reliability, observability, and close collaboration with product partners to move solutions from proof of concept through MVP and into production. What You’ll Build Agent-based solutions for: ○ Reconciliation workflows ○ Transaction insights and anomaly detection ○ Operational AI copilots ○ Systems that evolve from analytics and insights into decision support and autonomous execution The Role Agentic AI & LLM Engineering • Design, build, and deploy LLM-powered applications and multi-agent systems. • Architect agent workflows including memory strategies, tool integration, guardrails, and human-in-the-loop (HITL) patterns. • Implement retrieval-augmented generation (RAG) and context engineering using platforms such as Mem0 and Redis. Platform & Data Integration • Integrate agentic systems with enterprise data platforms, including TI, MEDI, and OR. • Develop reliable, scalable backend services using Python, APIs, and distributed system patterns. • Embed agentic intelligence into payment and operational workflows. Production Readiness & Reliability • Drive observability, evaluation, and system reliability for production AI services. • Implement monitoring and evaluation approaches to support availability, accuracy, and system performance. • Ensure AI systems meet enterprise standards for scalability, security, and operational excellence. Delivery, Product Partnership & Mentorship • Partner with Product to take solutions from proof of concept to MVP and production deployment. • Mentor engineers and establish best practices for agentic AI development. • Contribute to technical standards, patterns, and shared frameworks across the team. All About You • Strong experience building AI/ML or backend systems using modern engineering practices. • Hands-on experience developing LLM-powered applications, RAG pipelines, and agent-based systems. • Proven experience delivering production-scale services in distributed environments. • Strong proficiency in Python, APIs, and distributed systems design. • Ability to independently own complex technical problems and drive them to production. Technical Skills: • Retrieval and context strategies: RAG, vector-based retrieval • Engineering stack: Python, APIs, distributed systems, cloud-native platforms • Observability, evaluation, and reli