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 AI Designer– Agentic AI (L6)
Lead Agentic AI Designer & Developer(L6)
Agentic AI Product & Engineering, Operational Intelligence
Mastercard Services
Locations: Gurgaon, India | Pune, India
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Overview
Mastercard powers economies and empowers people in over 200 countries and territories worldwide. Together with our customers, we are helping build a sustainable economy where everyone can prosper.
Mastercard Services provides cutting-edge services across data, analytics, consulting, loyalty, fraud, cyber intelligence, and operational intelligence.
Within Business & Markets Insights (BMI), the Operational Intelligence (OI) team is building the next generation of AI-native products powered by LLMs, intelligent workflow automation, contextual memory, and autonomous reasoning systems to help customers identify, diagnose, and resolve complex payment operational issues faster and with greater precision.
As part of this transformation, we are seeking a Lead Agentic AI Designer & Developer to design, build, and scale enterprise-grade intelligent AI systems that combine large language models, advanced orchestration, memory frameworks, and production-grade engineering.
This is a highly hands-on role for an experienced builder who can translate complex business workflows into scalable autonomous AI products and bring them from concept to production.
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Role
• Design and develop intelligent AI systems capable of reasoning, diagnostics, anomaly detection, workflow automation, and operational recommendations across Mastercard’s Operational Intelligence product suite.
• Build modular LLM-driven workflows for planning, retrieval, summarization, tool execution, classification, and autonomous decision support.
• Develop stateful and deterministic execution flows with routing logic, fallback handling, confidence scoring, guardrails, retry mechanisms, and human-in-loop intervention.
• Engineer reusable AI orchestration services using frameworks such as LangGraph, LangChain, OpenAI Agent SDK, AutoGen, Strands, AgentCore, Semantic Kernel, or equivalent technologies.
• Design and implement contextual memory systems including session memory, long-term memory, semantic/vector memory, episodic memory, and graph-based relationship memory.
• Build enterprise grounding and retrieval capabilities leveraging RAG, Graph RAG, structured retrieval, enterprise APIs, and deterministic tool-based integrations.
• Develop Python/FastAPI based backend services, APIs, and microservice components to support enterprise-scale AI workflow execution.
• Build secure integrations with operational data stores, event streams, internal systems, enterprise services, and external model endpoints.
• Partner with Product Management and domain SMEs to convert customer problems and product use cases into scalable technical AI workflows and reusable product components.
• Collaborate with UX and frontend teams to design trustworthy AI interaction experiences including evidence layers, confidence indicators, decision traces, action recommendations, and audit visibility.
• Build rigorous evaluation and testing frameworks to measure model quality, hallucination rates, retrieval quality, workflow success, latency, reliability, and operational cost.
• Mentor junior engineers and contribute to reusable engineering standards, internal frameworks, and best practices for Mastercard’s growing AI-native product portfolio.
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All About You
• Strong software and backend engineering foundation with 7+ years of experience building scalable enterprise applications or AI-driven systems.
• 3+ years of hands-on experience building LLM applications, intelligent automation workflows, autonomous agents, or enterprise AI reasoning systems.
• Proven experience taking at least one AI/ML or LLM-based product from prototype to production deployment.
• Strong hands-on development expertise in Python, APIs, distributed systems, asynchronous services, and microservice-based architectures.
• Experience working with agent orchestration or LLM application frameworks such as LangGraph, LangChain, OpenAI Agent SDK, AutoGen, Strands, Semantic Kernel, AgentCore, or similar technologies.
• Hands-on experience with memory and retrieval systems such as Redis, Postgres, Pinecone, LanceDB, Mem0, Neo4j, Elasticsearch, or equivalent platforms.
• Experience building RAG, Graph RAG, or grounded enterprise retrieval workflows.
• Familiarity with enterprise deployment patterns using Docker, Kubernetes, CI/CD pipelines, and cloud environments such as AWS or Azure.
• Experience with evaluation, benchmarking, and observability tooling for AI applications such as Promptfoo, LangSmith, OpenTelemetry, Grafana, Signoz, or equivalent.
• Strong understanding of building AI systems with deterministic fallback, reliability controls, explainability, and human oversight.
• Ability to work across product, engineering, UX, domain SMEs, and platform teams in a highly collaborative environment.
• Strong problem-solving mindset with demonstrated ability to operate in a fast-moving 0→1 product development setting.
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Preferred Qualifications
• Prior experience in payments, reconciliation, fraud, compliance, financial operations, or operational intelligence platforms.
• Experience designing context-aware or stateful autonomous systems.
• Exposure to Graph RAG, knowledge graphs, or advanced memory orchestration.
• Familiarity with production-grade AI observability, agent performance tuning, and LLM cost optimization.
• Experience contributing to reusable internal AI frameworks or platform accelerators.
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Why This Role Matters
This role will help define how Mastercard builds the next generation of AI-native operational products — moving beyond traditional analytics into intelligent systems that can reason, guide, and automate complex operational workflows for customers globally.
You will have the opportunity to work on frontier LLM technologies while solving high-scale enterprise problems in one of the world’s most trusted payments ecosystems.
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Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks come 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.
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.