Senior 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. Title and Summary Senior AI Engineer Overview We are looking for a talented Senior AI Engineer to work with our Foundry Research and Development team to build innovative products delivered at scale to global markets. Role • Contributes to the design and development of scalable AI/ML systems and solutions to address complex business needs, ensuring adherence to best practices. • Implements models into production environments, designing scalable training pipelines and deployment frameworks. • Ensures operational stability and scalability of AI systems, contributing to the organization’s AI infrastructure and ethical standards. • Automates workflows for model training, testing, deployment, and updates, following CI/CD best practices. • Assists with the building and refining of data ingestion, preprocessing, and feature engineering workflows to support model training and inference. • Conducts hyperparameter tuning and validation to meet targeted performance metrics, ensuring robustness and efficiency for AI/ML models. • Monitors model performance, manages versioning, and updates models to maintain high-quality outputs. • May contribute to solution development for new products/services and/or manage smaller project/initiatives as an experienced individual contributor with specialized knowledge within the AI Engineering area. All About You: • Multiple years of relevant experience in AI and Data Science. • Enjoy building innovative solutions in a collaborative, fast-paced environment. • Possess advanced knowledge of modern software engineering principles and methodologies. • Be passionate about code quality and software engineering best practices. • Demonstrate initiative and a willingness to take on complex, challenging problems. • Exhibit excellent verbal and written communication skills with strong collaboration abilities. • Be highly motivated, driven, and a strong team player. • Be able to work independently, make sound decisions, and solve problems with minimal supervision. Skills • Strong experience building Agentic AI applications using frameworks such as LangGraph, CrewAI, and AutoGen, with solid understanding of Agentic AI design patterns, Context Management, LLMOps, AgentOps, Guardrails, Agent Validation, and Evaluation. • Hands-on experience with prompt engineering and working with both closed-source and open-source LLMs. • Experience applying RAG, few-shot prompting, LLM fine-tuning, and hybrid approaches to improve model context and performance. • Good working knowledge of MLOps tools, including MLflow. • Hands-on experience with LLM fine-tuning techniques. • Strong experience with Retrieval Augmented Generation (RAG), vector databases, and semantic search. • Proven experience designing and maintaining CI/CD pipelines to automate integration, testing, and deployment, ensuring reliable and high-velocity delivery. • Proficiency in Python and the data science ecosystem, including NumPy, pandas, sklearn, spaCy, Keras, PyTorch, Transformers, and LangGraph. • Strong understanding of Machine Learning, Deep Learning, and NLP concepts and models across supervised and unsupervised learning. • Working knowledge of Python-based API frameworks such as FastAPI, with comfort handling JSON-based services. • Thorough understanding of PySpark with a conceptual understanding of parallel and distributed processing for large-scale data. • Experience using Unix/Linux commands to access systems, manage databases, and deploy and op ... (truncated, view full listing at source)