Title and Summary
Principal AI Engineer
Overview
Mastercard Foundry is a global innovation group focused on the evolution of technology and consumer trends and how these changes impact the payments and commerce industry. Foundry is a collective of interdisciplinary teams powering Mastercard's ability to create and deliver differentiated products, services, and experiences. Within Foundry, the global Research and Development (R&D) team conducts applied research on emerging technologies to create innovative products for Mastercard. Foundry R&D is made up of talented, passionate developers, engineers, scientists, designers, researchers, data specialists, and program managers. We build knowledge in emerging technologies like agentic AI, generative AI and machine learning to conceptualize and create new products and services, which we then market test with our customers. We also bring the knowledge of cutting and bleeding edge technology to create concepts of the future which not only inspires our customers but also fosters the culture of innovation within Mastercard.
Role
As a Principal AI Engineer at Mastercard, you will be a key member of our AI delivery team, responsible for designing, building, and scaling AI microservices that transform proof-of-concept (PoC) notebooks into robust, production-ready components. Working closely with data scientists, MLOps engineers, and cross-functional partners, you will enable the seamless integration of AI services into the broader Mastercard ecosystem. This role offers a unique opportunity to bridge engineering and AI best practices in Applied AI.
Key Responsibilities
AI Microservice Design: Design and lead implementation of AI-powered microservices (e.g., ML, agentic AI) with a focus on modularity, scalability, and reusability to support diverse business units and solutions.
Productionalization: Transition AI models and agentic workflows from notebook-based PoCs to production-grade components, ensuring performance, reliability, and maintainability.
API Development: Design and lead implementation of robust APIs for AI microservices to facilitate seamless integration within the Mastercard ecosystem.
Quality Assurance: Lead the development of testing strategies (unit, integration, performance) to ensure the accuracy, stability, and quality of deployed AI services.
Performance Optimization: Identify and address bottlenecks in AI microservices and infrastructure, optimizing for latency, throughput, and cost efficiency.
Pipeline Development: Work with data science and infrastructure teams to design reusable workflows (e.g., feature engineering, model & agent optimization, evaluation pipelines).
Cross-Functional Collaboration: Partner with data scientists, MLOps engineers, product owners, and external stakeholders to translate business requirements into technical specifications.
Technology Innovation: Research and evaluate emerging technologies (e.g., LLMs, frameworks, methodologies) to enhance AI software development and large-scale data processing capabilities.
Compliance & Ethics: Ensure all AI microservices adhere to Mastercard’s security standards, compliance policies, and ethical AI principles, while contributing to AI engineering best practices.
Qualifications
Education: Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field. Master’s degree preferred.
Experience: Minimum of 10+ years in software development, with at least 5 years focused on building and deploying AI/ML, GenAI, AgenticAI powered applications or microservices in production environments.
Technical Skills
Strong proficiency in Python, Java and relevant frameworks (e.g., Spring Boot, Spring AI, FastAPI, LangChain, LangGraph, Semantic Kernel).
Extensive experience designing, developing, and deploying RESTful APIs and microservices.
Proficiency with containerization technologies.
Proven experience delivering GenAI, Agentic AI workflows in production.
Proven experience scaling machine learning models from prototype to production, including familiarity with feature stores, model registries, and inference patterns.
Solid understanding of the AI/ML lifecycle, from data preparation and model training to deployment and monitoring.
Experience with cloud platforms and their relevant compute, storage, and AI/ML services, cloud certification preferred.
Solid understanding of ML, Deep Learning.
Solid understanding of neural network and transformer model architecture.
Solid experience of CI/CD pipelines for automated testing and deployment of software and AI models.
Understanding of data governance, data quality, and data security principles relevant to AI/ML applications.
Excellent communication, interpersonal, and stakeholder management skills, with the ability to effectively articulate complex technical concepts to both technical and non technical audiences.
Corporate Security Responsibility
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.
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