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, OpenAI Agent SDK
• Retrieval and context strategies: Graph RAG, vector search, embeddings, MCP
• Large language models: GPT-4o, Claude, LLaMA, Mistral, enterprise LLMsTechnology stack: Python, SQL, APIs, Kubernetes, Docker, FastAPI, MongoDB, Redis
• AI system evaluation, monitoring, and observability

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.

Pay Ranges
Purchase, New York: $179,000 - $305,000 USD