Mastercard

Overview

The AI Engineer is responsible for designing, developing, and operationalizing enterprise-grade AI and Generative AI solutions that deliver measurable business value while ensuring scalability, security, governance, and regulatory compliance.

About Mastercard

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.

Requirements & Eligibility

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, Data Science, or a related technical field.
• Experience in designing, developing, and deploying AI, Generative AI, or machine learning solutions in production environments.
• Hands-on experience building LLM applications, Agentic AI systems, and RAG architectures from concept through deployment.
• Strong expertise with GenAI ecosystems and frameworks such as OpenAI, Azure OpenAI, Gemini, Hugging Face, LangChain, LangGraph, and open-source foundation models.
• Strong Python programming skills with experience developing APIs, microservices, and production-ready AI applications.

Key Responsibilities

• Design, develop, and deploy AI/ML, Generative AI, and Agentic AI solutions to solve complex business problems and improve operational efficiency.
• Build and maintain Large Language Model (LLM) applications, Retrieval-Augmented Generation (RAG) pipelines, intelligent agents, and multimodal AI solutions from prototype through production deployment.
• Design AI agent architectures, orchestration frameworks, and inter-agent communication protocols to automate business and technology workflows.
• Develop scalable backend services, API layers, and supporting technical components required to operationalize AI solutions.
• Implement MLOps and LLMOps practices to support deployment, monitoring, quality assurance, reproducibility, and lifecycle management of AI solutions.