Lead Agentic AI Designer

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.

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.

• Reconciliation workflows
• Transaction insights and anomaly detection
• Operational AI copilots
• Systems that evolve from analytics and insights into decision support and autonomous execution

• 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.

• 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.

• 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.

• 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.

• 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.

• Retrieval and context strategies: RAG, vector-based retrieval
• Engineering stack:
  Python, APIs, distributed systems, cloud-native platforms
• Observability, evaluation, and reliability for AI systems

• 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.…