Mastercard is hiring for an exciting AI Engineer opportunity in Pune under its AI & Data category. This is a full-time role, Job ID: R-279646, and can be particularly attractive to freshers and early-career candidates who have strong academic projects, hands-on Generative AI experience, or practical AI/ML development skills.
If you have worked with Python, SQL, GenAI, LLMs, RAG, Agentic AI, LangChain, cloud platforms, Databricks, Docker, Kubernetes, or MLOps, this opportunity deserves your attention. 🎯
đź“Ś Mastercard AI Engineer
• Company: Mastercard
• Role: AI Engineer
• Job ID: R-279646
• Location: Pune, Maharashtra – 411006
• Job Type: Full-time
• Experience: Freshers / Early Career candidates with strong AI projects can apply
• Education: Bachelor’s degree in Computer Science, Data Science, AI/ML, or related field
• Expected CTC: ₹15–25 LPA*
• Category: AI & Data
🏢 About Mastercard
Mastercard is a global technology company operating in the payments industry and connecting people and organizations across more than 210 countries and territories. Its technology, data, payment networks, cybersecurity, fraud prevention, and digital solutions support businesses, financial institutions, governments, and consumers worldwide.
Mastercard is also heavily investing in Artificial Intelligence. The company says AI has been part of its innovation journey for more than a decade, using data and AI to improve areas such as fraud detection, security, and personalization. Mastercard’s AI initiatives also emphasize responsible AI, including governance, fairness, and reducing bias.
🤖 Why This Role Is Excellent for Early-Career Experience
This is not a role limited to building ML models. The JD covers the complete AI engineering lifecycle—data preparation, LLM applications, RAG, agentic AI, APIs, cloud integration, deployment, monitoring, MLOps/LLMOps, and Responsible AI.
For a fresher, this breadth can provide exposure to modern production-oriented AI engineering rather than only academic model training. You could develop experience connecting AI applications with databases and APIs, deploying containerized services, working with cloud platforms, and thinking about reliability and monitoring.
The strongest differentiator is the Responsible AI requirement. Candidates are expected to understand hallucination mitigation, bias detection, explainability, output guardrails, and data ethics. This makes the role particularly valuable for candidates who want to build enterprise-grade AI systems.
🧠Skills Required
• Python programming and software engineering fundamentals
• SQL and data manipulation
• Generative AI and LLM fundamentals
• Prompt engineering
• RAG architecture and semantic search
• Vector databases and embeddings
• Agentic AI and tool/function calling
• LangChain, LangGraph, or similar orchestration frameworks
• Spark and data-processing concepts
• AWS/Azure and cloud AI services
• Databricks or Microsoft Fabric
• Docker and basic Kubernetes
• APIs and cloud integrations
• ETL/data pipelines
• Git and SDLC
• MLOps/LLMOps concepts
• Model evaluation and monitoring
• Responsible AI and AI governance
• Strong analytical and communication skills
🎯Preparation Tips
1. Build one end-to-end RAG project: Don’t simply create a chatbot. Build a document Q&A system using embeddings, a vector database, retrieval, reranking if applicable, an LLM, citations, and an evaluation approach. Be ready to explain why you selected each component.
2. Prepare an Agentic AI use case: Create a small agent that can call tools such as a database/API or calculator. Understand tool calling, agent memory, orchestration, failure handling, and permissions.
3. Master Responsible AI: For this JD, prepare scenarios around hallucination, prompt injection, sensitive data, biased outputs, unsafe responses, explainability, and human oversight. Mastercard explicitly emphasizes responsible and safe AI development.
4. Know production deployment: Be able to explain how your AI application moves from local development to Docker → cloud → monitoring. Revise logging, latency, scalability, API security, model/version tracking, and basic Kubernetes concepts.
5. Strengthen SQL + Python: Expect practical questions rather than only definitions. Practice Python data manipulation, dictionaries, lists, functions, OOP basics, Pandas, and SQL joins, CTEs, aggregations, and window functions.
đź’¬ Expected Mastercard Interview Rounds
Round 1 – Online Assessment/Karat: Coding and problem-solving may be assessed.
Round 2 – Technical Interview: Projects, programming, SQL, APIs, databases, and technical fundamentals. Recent Pune reports specifically mention project/tech-stack discussions, OOP, SQL, APIs, and scenario-based questions.
Round 3 – Technical/AI Deep Dive: For this particular role, prepare for LLMs, RAG, GenAI architecture, cloud, data pipelines, deployment, and Responsible AI.
Round 4 – HR/Managerial: Communication, motivation, teamwork, problem-solving, and why Mastercard/AI engineering.
đź’° Salary Range
The advertised social post indicates an expected CTC of ₹15–25 LPA, but this should be treated as an estimate rather than an official Mastercard salary band. Public salary data for Mastercard AI/ML Engineer roles in Pune has previously shown approximately ₹14.3–15.6 LPA base pay, although that dataset has low confidence and is based on very limited submissions.
Given the JD’s GenAI, cloud, RAG, and production-AI requirements, candidates should focus more on role fit than assuming a guaranteed â‚ą25 LPA package.
đź“„ Resume Tips for This JD
Make your resume look like an AI Engineer resume, not a generic fresher resume.
Your headline can be:
“AI/ML Engineer | Python | GenAI | LLM | RAG | Agentic AI | Cloud | MLOps”
Prioritize projects involving LLMs, RAG, vector databases, LangChain/LangGraph, APIs, cloud deployment, Docker, Databricks, or MLOps.
đź“© How to Apply
👉 Application Link: Click Here
🤝 Referral Tip
Want to improve your chances of getting noticed?
Connect with someone at Mastercard and request a referral—it can significantly enhance your visibility in the hiring process.
Search for Mastercard AI Engineer – Job ID R-279646 on the official Mastercard Careers portal and submit your application through the company’s hiring system. Also verify that the job is still active before applying.
🚀 Final Verdict
For freshers serious about entering Generative AI and AI Engineering, this Mastercard opportunity stands out because the JD goes beyond basic ML and covers LLMs, RAG, Agentic AI, cloud, data engineering, MLOps, deployment, and Responsible AI. Build one strong end-to-end AI project, understand what happens after development, and be prepared to explain your technical decisions clearly. That combination can make your profile much stronger than simply listing GenAI keywords.
