Lead the architecture of AI systems, build data pipelines, implement multi-agent frameworks, and manage product engineering teams for enterprise AI solutions.
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 & Lead AI Designer
Director- Agentic AI Architect & Lead AI Designer
Enterprise AI Product Engineering
Overview
Mastercard Services' Operational Intelligence (OI) team is expanding its AI platform with agentic AI and LLM-driven autonomous systems. We are seeking a Director-level Agentic AI Architect & Developer to design, build, and scale enterprise-grade multi-agent platforms.
This role starts as a hands-on individual contributor, owning architecture and delivery end-to-end, and evolves into people leadership after the first successful launch.
Key Responsibilities
1. Agentic Architecture & Engineering
2. Architect and build multi-agent LLM systems using LangGraph, LangChain, AutoGen, AgentCore, Strands, and OpenAI Agent SDK.
3. Design stateful, deterministic, and fault-tolerant workflows with guardrails, routing, and recovery logic.
4. Build modular agent systems for classification, routing, reconciliation, anomaly detection, and reasoning.
Memory, Reasoning, Graph RAG & MCP
1. Implement short-term, long-term, vector, semantic, episodic, and graph memory.
2. Design and build Graph RAG pipelines using knowledge graphs for grounded reasoning.
3. Develop MCP (Model Context Protocol) servers and tools to expose secure, governed data and actions to agents.
4. Define structured reasoning paths, execution graphs, and evaluation frameworks for accuracy, grounding, latency, and drift.
Model, Data & Platform Integration
1. Integrate enterprise and open-source LLMs (GPT-4o, Claude, LLaMA, Mistral, internal models).
2. Build ingestion pipelines and backend services using Python, FastAPI, MongoDB, Redis, and event-driven systems.
3. Embed agentic intelligence into Mastercard's Operational Intelligence platforms.
Production & Collaboration
1. Deploy on AWS EKS / Azure AKS with CI/CD and full observability (OpenTelemetry, Prometheus, Grafana).
2. Partner with product, platform, MLOps, and domain SMEs to translate operational workflows into AI systems.
3. After launch, build and lead a high-impact AI engineering team.
Qualifications
Must-Have Experience
1. Led architecture and delivery of at least one MVP of an enterprise agentic AI product, with scaling experience from 0→1 in an enterprise environment.
2. Hands-on experience building Graph RAG systems using knowledge graphs.
3. Hands-on experience developing MCP servers, tools, and schemas for agent-tool interaction.
4. 7-10 years in AI/ML engineering with strong focus on LLMs and agentic systems.
5. Proven experience deploying multi-agent systems and AI/ML products in production.
6. Strong foundation in distributed systems and microservices.
Technical Skills
1. Agentic frameworks: LangGraph, LangChain, AutoGen, AgentCore, OpenAI Agent SDK.
2. Retrieval & Context: Graph RAG, vector search, embeddings, MCP.
3. LLMs: GPT-4o, Claude, LLaMA, Mistral, enterprise models.
4. Stack: Python, SQL, APIs, Kubernetes, Docker, FastAPI, MongoDB, Redis.
5. Evaluation and observability for AI systems.
Preferred
Experience in payments, operational intelligence, reconciliation, fraud/AML, compliance, or disputes.
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:
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 & Lead AI Designer
Director- Agentic AI Architect & Lead AI Designer
Enterprise AI Product Engineering
Overview
Mastercard Services' Operational Intelligence (OI) team is expanding its AI platform with agentic AI and LLM-driven autonomous systems. We are seeking a Director-level Agentic AI Architect & Developer to design, build, and scale enterprise-grade multi-agent platforms.
This role starts as a hands-on individual contributor, owning architecture and delivery end-to-end, and evolves into people leadership after the first successful launch.
Key Responsibilities
1. Agentic Architecture & Engineering
2. Architect and build multi-agent LLM systems using LangGraph, LangChain, AutoGen, AgentCore, Strands, and OpenAI Agent SDK.
3. Design stateful, deterministic, and fault-tolerant workflows with guardrails, routing, and recovery logic.
4. Build modular agent systems for classification, routing, reconciliation, anomaly detection, and reasoning.
Memory, Reasoning, Graph RAG & MCP
1. Implement short-term, long-term, vector, semantic, episodic, and graph memory.
2. Design and build Graph RAG pipelines using knowledge graphs for grounded reasoning.
3. Develop MCP (Model Context Protocol) servers and tools to expose secure, governed data and actions to agents.
4. Define structured reasoning paths, execution graphs, and evaluation frameworks for accuracy, grounding, latency, and drift.
Model, Data & Platform Integration
1. Integrate enterprise and open-source LLMs (GPT-4o, Claude, LLaMA, Mistral, internal models).
2. Build ingestion pipelines and backend services using Python, FastAPI, MongoDB, Redis, and event-driven systems.
3. Embed agentic intelligence into Mastercard's Operational Intelligence platforms.
Production & Collaboration
1. Deploy on AWS EKS / Azure AKS with CI/CD and full observability (OpenTelemetry, Prometheus, Grafana).
2. Partner with product, platform, MLOps, and domain SMEs to translate operational workflows into AI systems.
3. After launch, build and lead a high-impact AI engineering team.
Qualifications
Must-Have Experience
1. Led architecture and delivery of at least one MVP of an enterprise agentic AI product, with scaling experience from 0→1 in an enterprise environment.
2. Hands-on experience building Graph RAG systems using knowledge graphs.
3. Hands-on experience developing MCP servers, tools, and schemas for agent-tool interaction.
4. 7-10 years in AI/ML engineering with strong focus on LLMs and agentic systems.
5. Proven experience deploying multi-agent systems and AI/ML products in production.
6. Strong foundation in distributed systems and microservices.
Technical Skills
1. Agentic frameworks: LangGraph, LangChain, AutoGen, AgentCore, OpenAI Agent SDK.
2. Retrieval & Context: Graph RAG, vector search, embeddings, MCP.
3. LLMs: GPT-4o, Claude, LLaMA, Mistral, enterprise models.
4. Stack: Python, SQL, APIs, Kubernetes, Docker, FastAPI, MongoDB, Redis.
5. Evaluation and observability for AI systems.
Preferred
Experience in payments, operational intelligence, reconciliation, fraud/AML, compliance, or disputes.
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.
Top Skills
BigQuery
Datadog
Kafka
Langchain
Langgraph
Llm Engineering
Opentelemetry
Pinecone
Redis
Redshift
Snowflake
SQL
Vespa
Weaviate
Mastercard Pune, Mahārāshtra, IND Office



Poona Club Road, Pune, Maharashtra, India, 411001
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