AI Engineer
Mastercard20 hours ago
Pune, IndiaStaff+
Responsibilities
- Architect and lead multi-agent AI systems using LangGraph, CrewAI, and AutoGen for autonomous reasoning, tool use, coordination, and decision-making.
- Design and operationalize multimodal generative AI pipelines using transformer-based models across text, image, tabular, and graph data.
- Build production-grade RAG and Graph-RAG systems with vector databases and knowledge graphs.
- Lead LLM fine-tuning, prompt engineering, model alignment, RLHF, PEFT, LoRA, and instruction-tuning strategies.
- Establish LLMOps and MLOps pipelines with model evaluation, lineage tracking, feature stores, and continuous retraining.
- Develop Python backend and inference services for orchestration, asynchronous jobs, streaming responses, and distributed data workflows.
- Engineer agent state, memory, context management, and cross-tool or cross-modal coordination systems.
- Implement responsible AI, governance, safety, explainability, bias detection, and hallucination mitigation practices.
- Apply traditional machine learning and statistical modeling in hybrid systems alongside LLMs.
- Research, evaluate, benchmark, and productionize advances in generative modeling, agentic AI, multimodal transformers, and foundation models.
Requirements
- Master’s or bachelor’s degree in Computer Science, AI/ML, or Engineering.
- Significant hands-on experience leading and delivering complex generative AI or ML engineering programs in production environments.
- Expert hands-on experience designing, building, and deploying LLM applications, agentic systems, and RAG pipelines from prototype through production.
- Deep proficiency with OpenAI, Anthropic, Gemini, Hugging Face, LangChain/LangGraph, and open-source foundation models such as LLaMA, Mistral, and Falcon.
- Strong knowledge of prompt engineering, chain-of-thought reasoning, tool or function calling, vector embeddings, semantic search, and agent memory architectures.
- Applied knowledge of predictive modeling, deep learning with PyTorch and TensorFlow, and statistical techniques.
- Advanced Python skills, including asynchronous programming, API development with FastAPI, and inference-ready microservices; SQL proficiency is required.
- Hands-on experience with AWS SageMaker, Amazon Bedrock, Azure OpenAI, or Google Cloud Vertex AI.
- Familiarity with MLOps and LLMOps tooling such as MLflow and Weights & Biases.
- Strong analytical, communication, and stakeholder-management skills with the ability to lead cross-functional delivery.
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).