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AI Engineer

MastercardPosted todayLast checked Aug 9, 2026
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📍 Gurgaon, India
💼 2 Years
Full-time
🎓 Any Batch
🚀 Engineering
💰30 - 40 LPA

🏢 About Mastercard

Mastercard is a leading organization in the technology and services industry, committed to driving innovation and digital transformation. They provide a dynamic and supportive environment for early-career professionals to learn, collaborate, and build solutions at scale. Freshers at Mastercard are integrated into production teams with structured onboarding and mentorship.

Job Details & Requirements

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Job Description

AI Engineer

Location Gurgaon, India, 122002Category AI & DataJob Type Full timeJob Id R-287145End Date: 2026-08-30

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

AI Engineer 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.

Job Title

AI Engineer

Overview:

The Global Pricing & Interchange (P&IC) team plays a critical role in shaping Mastercard’s economics strategy and enabling profitable growth across products, services, and markets. The team partners with regional and global business units to execute pricing and interchange strategies under a consistent global framework while driving revenue optimization, commercial simplification, enhanced customer experiences, and strategic transformation initiatives.

As an AI Engineer, you will play a pivotal role in advancing the team's vision of leveraging Artificial Intelligence, Generative AI, and emerging technologies to improve decision-making, operational efficiency, and business outcomes. You will design, build, and deploy scalable AI solutions, including Large Language Models (LLMs), Agentic AI systems, Retrieval-Augmented Generation (RAG) frameworks, and intelligent automation capabilities that transform complex business challenges into actionable insights and automated workflows.

Working closely with global business, analytics, and technology stakeholders, you will drive the adoption of AI-powered solutions, establish engineering best practices, and help shape the future of AI-enabled decision-making across the Global Pricing & Interchange organization.

Role:

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.

🎯 What Success Looks Like in This Role

  • 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.

  • Collaborate with business stakeholders, product owners, and domain experts to identify high-impact AI opportunities and translate business requirements into technical solutions.

  • Build and maintain cloud-native AI/ML pipelines, model deployment frameworks, and data integration workflows using modern AI platforms and cloud technologies.

  • Implement MLOps and LLMOps practices to support deployment, monitoring, quality assurance, reproducibility, and lifecycle management of AI solutions.

  • Evaluate emerging AI technologies, frameworks, and tools through proofs of concept and rapid prototyping.

  • Ensure all AI solutions adhere to Mastercard's security, privacy, responsible AI, and governance standards.

  • Implement Responsible AI controls including bias monitoring, hallucination mitigation, explainability, model validation, and AI safety guardrails.

  • Partner across analytics, engineering, product, and business teams to identify AI integration opportunities and drive enterprise adoption of AI capabilities.

  • Communicate technical concepts, solution designs, and business value effectively to both technical and non-technical audiences.

All About You:

  • 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.

  • Deep understanding of prompt engineering, vector embeddings, semantic search, agent orchestration, reasoning frameworks, and AI application architecture.

  • Strong Python programming skills with experience developing APIs, microservices, and production-ready AI applications.

  • Experience with SQL and large-scale data processing technologies including Spark and modern cloud data platforms.

  • Experience working with Azure, AWS, Databricks, Microsoft Fabric, or other cloud-based AI and data platforms.

  • Knowledge of MLOps, LLMOps, CI/CD pipelines, model deployment, monitoring, and version control practices.

  • Familiarity with APIs, data pipelines, cloud integrations, and enterprise application development.

  • Understanding of machine learning fundamentals, predictive modeling, deep learning frameworks (TensorFlow, PyTorch), and statistical techniques.

  • Experience implementing Responsible AI practices, model governance, explainability, fairness, and AI risk management frameworks.

  • Strong analytical, problem-solving, and critical-thinking capabilities.

  • Excellent communication and stakeholder management skills, with the ability to translate complex AI concepts into business value.

  • Ability to manage multiple priorities, work independently, and thrive in a fast-paced and evolving technology environment.

  • Financial services, fintech, payments, pricing, or analytics experience is highly desirable.

  • Passion for innovation, emerging technologies, and continuous learning in the rapidly evolving AI landscape.

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.

Recommended Technical Skills
AIGenerative AIMachine LearningPythonSQLSparkCloud-based AI and data platformsMLOpsLLMOpsCI/CD pipelinesmodel deploymentmonitoringand version control practicesAPIs

🎓 Preparation & Hiring Insights

Verified Insights
💰 Salary Insights (India)
Industry Range

The average salary for an AI Engineer in the industry is between 25-40 LPA

Freshers

The average salary for a fresher AI Engineer is between 15-25 LPA

Experienced

The average salary for an experienced AI Engineer is between 30-50 LPA

⚡ Selection Rounds

1
Round 1: Resume screening and initial phone screening
2
Round 2: Technical interview with a focus on AI, machine learning, and programming skills
3
Round 3: Behavioral interview with a focus on teamwork, communication, and problem-solving skills

💡 Top Interview Questions to Prepare

  1. What is your experience with AI and machine learning?
  2. How do you approach building and deploying AI models?
  3. Can you explain the concept of Generative AI?
  4. How do you handle imbalanced datasets?
  5. What is your experience with cloud-based AI and data platforms?

Frequently Asked Questions

The salary range for this role is between 30-40 LPA
The key skills required for this role are AI, machine learning, programming languages such as Python and Java, cloud-based AI and data platforms, MLOps and LLMOps, and CI/CD pipelines
The career path for an AI Engineer can include roles such as Senior AI Engineer, AI Architect, and AI Researcher

CampusToCareer Candidate Guide

⭐ Original Analysis

✓ Suitable For

  • Computer Science graduates
  • Self-taught coders with strong portfolios
  • Students interested in software development

✗ Not Ideal If

  • Seeking non-technical support roles
  • Comfortable only with drag-and-drop tool designs