Lead Agentic AI Designer

Mastercard Inc.; Purchase (NY); On-site; USD 150,000 - 254,000; Full time

Benefits offered by this job

Health insurance

Paid time off

401k with match

Tuition reimbursement

Job summary

Mastercard Inc. is expanding its AI platform within the Operational Intelligence team to design, build, and scale enterprise-grade, multi-agent AI systems.

The Lead AI Engineer will own architecture and delivery, with potential progression to people leadership as the project moves beyond MVP to production. You will design and deploy large-scale LLM applications, integrate with enterprise data platforms, and ensure production readiness, reliability, and security.

Qualifications

• 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.

Responsibilities

• Design, build, and deploy LLM-powered applications and multi-agent systems.
• Architect agent workflows including memory strategies, tool integration, guardrails, and HITL patterns.
• Develop reliable, scalable backend services using Python, APIs, and distributed system patterns.
• Embed agentic intelligence into payment and operational workflows.

Skills

Python

Distributed systems

APIs

LLM/Agentic AI

Production readiness

Tools

Mem0

Redis

Job description

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

• 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

• 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 reliability for AI systems

Preferred Qualifications

• Experience with agentic AI systems and autonomous workflows
• Exposure to fintech, payments, or regulated environments
• Experience with vector or graph databases
• Cloud deployment experience

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [e-mail] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience.

Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more.

Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.

THIS POSTING RELECTS ONE OR MORE CURRENT VACANCIES ON OUR TEAM, AND MASTERCARD INTENDS TO FILL THIS POSITION BY 07/27/2026.

Pay Ranges Purchase, New York: $150,000 - $254,000 USD

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.