Principal AI Engineer Job at Mastercard (Dublin 18)

Principal AI Engineer

Mastercard

Location:
Ireland , Dublin 18

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

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. To support this range of projects we are looking for a talented Principal AI Engineer to join the Mastercard Foundry R&D team in our Dublin TechHub. 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.

Job Responsibility:

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

Requirements:

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field. Master’s degree preferred
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
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

Additional Information:

Job Posted:
March 26, 2026

Expiration:
April 30, 2026

Employment Type:

Fulltime

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