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

Mastercard is the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee can be a part of something bigger and change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities.

Join a fast-growing team

As an AI Engineer within Mastercard's AI Foundations team, you will build the platforms, services, and data infrastructure that enable AI at enterprise scale. You will develop systems that support the full AI lifecycle, from data ingestion and processing to model deployment, evaluation, monitoring, and governance.

Working with large-scale transactional and operational datasets, you will design and implement resilient data pipelines, distributed processing frameworks, and production-grade software services that power AI applications across Mastercard. You will collaborate with data scientists, product teams, and platform engineers to transform research and prototypes into secure, scalable, and maintainable production systems.

The role combines software engineering and data engineering, with a focus on building high-performance systems using technologies such as Python, Spark, SQL, Hive, Impala, cloud-native services, containerized workloads, and modern data platforms.

Your Role:

• Design, build, and operate production-grade AI and ML services, APIs, libraries, and reusable platform components.
• Own end-to-end AI engineering workflows, including data preparation, model integration, evaluation, deployment, monitoring, and continuous improvement.
• Support cloud migration efforts, transitioning on-premises data workflows to cloud-based platforms such as Databricks, Cloudera, Amazon AWS, etc.
• Collaborate with data scientists to improve feature selection, feature engineering, and enable end-to-end AI workflows from model training to deployment and monitoring.
• Develop CI/CD pipelines to streamline data pipeline deployments and ensure stable, automated workflows.
• Improve monitoring and observability to maintain system reliability.
• Work with data scientists, product teams, and platform engineers to align data solutions with business objectives.
• Ensure data quality, security, and compliance with industry standards.
• Contribute to best practices in data governance, documentation, and automation.

Ideal Candidate Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.
• Advanced Python and SQL skills, with strong software engineering fundamentals including modular design, APIs, testing, debugging, performance optimization, and maintainability.
• Experience leveraging open source tools, predictive analytics, machine learning, Advanced Statistics, and other data techniques to perform basic analysis
• High proficiency in using Python/Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi), SQL to build Big Data products & platforms
• Experience in building and deploying production-level data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale in Java, Scala, or Python and deliver analytics involving all phases like data ingestion, feature engineering, modeling, tuning, evaluating, monitoring, and presenting
• Curiosity, creativity, and excitement for technology and innovation
• Demonstrated quantitative and problem-solving abilities
• Ability to multi-task and strong attention to detail
• Motivation, flexibility, self-direction, and desire to thrive on small project teams
• Good communication skills - both verbal and written - and strong relationship, collaboration skills, and organizational skills

The following skills will be considered as a plus:

• Financial Institution or a Payments experience a plus
• Experience in developing integrated cloud applications with services like Azure, Databricks, AWS, or GCP
• Experience in managing/working in Agile teams

• Experience developing and configuring dashboards

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• 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.