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Director – AI Strategy & Product Management (Agentic AI)

mastercard · Pune

New
Senior 🇬🇧 English
LangGraph LangChain Graph RAG MCP-based systems

Job description

About the role

Mastercard’s Operational Intelligence team is building agentic AI and large‑language‑model driven platforms to transform payment operations. We are seeking a Director to lead AI strategy, product development, UX design, and execution of enterprise AI products, including multi‑agent systems, decision platforms, and autonomous workflows.

Key responsibilities

  • Define the agentic AI strategy and roadmap across Operational Intelligence.
  • Own the end‑to‑end product lifecycle from PRD through MVP to production.
  • Deliver AI products for reconciliation, disputes, and operational processes.
  • Specify requirements for multi‑agent systems (e.g., LangGraph, LangChain) and stateful workflows with guardrails and human‑in‑the‑loop controls.
  • Partner with engineering on LLMs, Retrieval‑Augmented Generation (RAG), Graph RAG, and MCP‑based architectures.
  • Design UI/UX beyond chat, including structured workflows, dashboards, and control panels.
  • Build trust, control, and observability layers for agent actions.
  • Establish and lead an AI Program Office, managing portfolio prioritization, capacity planning, and executive reporting.
  • Lead proof‑of‑concept to production pipelines, defining success metrics and avoiding common POC pitfalls.
  • Integrate LLMs (GPT, Claude, LLaMA) and enterprise data platforms, defining requirements for vector and graph retrieval and memory systems.

Required profile

  • Proven experience leading AI strategy and product management at an enterprise scale.
  • Hands‑on leadership in building AI products from concept to production.
  • Strong understanding of agentic AI, multi‑agent systems, and LLM technologies.
  • Experience establishing program offices and managing AI portfolios.

Required skills

  • LLMs such as GPT, Claude, LLaMA.
  • LangGraph and LangChain frameworks.
  • Retrieval‑Augmented Generation (RAG) and Graph RAG.
  • MCP‑based system design.
  • Vector and graph retrieval techniques.
  • Memory systems (short‑term, long‑term, semantic, graph).

Questions fréquentes

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Source : ats:workday

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