Director- Agentic AI Architect & 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. Title And Summary Director- Agentic AI Architect & AI Designer

The Services team and solutions fuel growth for partners globally by providing cutting edge services in the areas of Customer Acquisition and Engagement, Security Solutions, Business and Market Insights, and Open Banking. Focused on thinking big and scaling fast, our agile sales team is responsible for end-to-end solutions for a diverse global customer base including retailers, airlines, hotels, tourism agencies, public sector entities, restaurants, consumer goods and telecom companies.

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.

Role

The Director, Agentic AI Architect & AI Designer will lead the technical design and implementation of intelligent, autonomous systems using modern agentic frameworks and LLMs. The role partners closely with product, platform, and domain teams to translate complex operational requirements into production-ready AI solutions.

Agentic Architecture & Engineering

• Architect and develop enterprise-grade, multi-agent LLM systems using frameworks such as LangGraph, LangChain, AutoGen, AgentCore, Strands, and OpenAI Agent SDK.
• Design stateful, deterministic, and fault-tolerant agent workflows with guardrails, routing, and recovery logic.
• Build modular agent components for use cases including classification, routing, reconciliation, anomaly detection, and reasoning.

Memory, Reasoning, Graph RAG & Model Context

• Implement short-term, long-term, vector, semantic, episodic, and graph-based memory strategies.
• Design and develop Graph RAG pipelines using knowledge graphs to enable grounded and explainable reasoning.
• Build Model Context Protocol (MCP) servers and tools to securely expose governed data and actions to agents.
• Define structured reasoning paths, execution graphs, and evaluation frameworks to measure accuracy, grounding, latency, and model drift.

Model, Data & Platform Integration

• Integrate enterprise and open-source LLMs, including GPT‑4o, Claude, LLaMA, Mistral, and internal models.
• Develop ingestion pipelines and backend services using Python, FastAPI, MongoDB, Redis, and event-driven architectures.
• Embed agentic intelligence into Mastercard’s Operational Intelligence platforms.

Production, Delivery & Collaboration

• Deploy and operate systems on cloud-native infrastructure such as AWS EKS and Azure AKS using CI/CD pipelines and full observability tooling (OpenTelemetry, Prometheus, Grafana).
• Partner with product, platform, MLOps, and domain subject-matter experts to convert operational workflows into scalable AI systems.
• Following initial platform launch, build and lead a high-impact AI engineering team.

All About You

• Demonstrated experience leading the architecture and delivery of an enterprise agentic AI product from initial build through production scaling.
• Hands-on experience designing and implementing Graph RAG systems using knowledge graphs.
• Hands-on experience developing MCP servers, schemas, and tools for agent‑to‑tool interaction.
• Proven experience deploying AI/ML and multi-agent systems into production environments.
• Strong foundation in distributed systems and microservices architectures.
• Experience working in domains such as payments, operational intelligence, reconciliation, fraud/AML, compliance, or disputes is a plus.

Technical Skills

• Agentic frameworks and orchestration: LangGraph, LangChain, AutoGen, AgentCore, Op…