AI Engineer
Mastercard18 hours ago
Gurgaon, IndiaSenior
Responsibilities
- Design, develop, and deploy AI/ML, Generative AI, and Agentic AI solutions for complex business problems.
- Build and maintain LLM applications, RAG pipelines, intelligent agents, and multimodal AI solutions from prototype through production.
- Design agent architectures, orchestration frameworks, and inter-agent communication protocols.
- Develop scalable backend services, API layers, data integrations, and other components needed to operationalize AI solutions.
- Build cloud-native AI/ML pipelines, model deployment frameworks, and data integration workflows.
- Implement MLOps and LLMOps practices for deployment, monitoring, quality assurance, reproducibility, and lifecycle management.
- Evaluate emerging AI technologies through proofs of concept and rapid prototyping.
- Implement responsible AI controls for bias monitoring, hallucination mitigation, explainability, model validation, and safety guardrails.
- Partner with business, analytics, engineering, product, and domain stakeholders to identify AI opportunities and support enterprise adoption.
- Communicate technical designs, AI concepts, and business value to technical and non-technical audiences.
- Follow Mastercard security policies, protect information confidentiality and integrity, report suspected security violations, and complete required security training.
Requirements
- Bachelor’s or master’s degree in computer science, artificial intelligence, machine learning, engineering, data science, or a related technical field.
- Experience designing, developing, and deploying AI, Generative AI, or machine learning solutions in production.
- Hands-on experience building LLM applications, Agentic AI systems, and RAG architectures through deployment.
- Expertise with OpenAI, Azure OpenAI, Gemini, Hugging Face, LangChain, LangGraph, and open-source foundation models.
- Strong understanding of prompt engineering, vector embeddings, semantic search, agent orchestration, reasoning frameworks, and AI application architecture.
- Strong Python skills and experience developing APIs, microservices, and production-ready AI applications.
- Experience with SQL, Spark, and large-scale data processing or modern cloud data platforms.
- Experience 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, TensorFlow, PyTorch, and statistical techniques.
- Experience with responsible AI, model governance, explainability, fairness, and AI risk management frameworks.
- Strong analytical, problem-solving, critical-thinking, communication, and stakeholder management abilities.
- Ability to manage multiple priorities, work independently, and operate in a fast-paced technology environment.
- Financial services, fintech, payments, pricing, or analytics experience is highly desirable.
Categories
About Mastercard
Mastercard builds and operates a global payments network used by banks, merchants, fintechs, and governments, offering card processing, real-time payments, tokenization, and fraud/risk services. It generates revenue from transaction processing and assessment/service fees across more than 200 countries and territories. Founded in 1966 and headquartered in Purchase, New York, Mastercard is a public company listed on the NYSE (ticker: MA).