Lead AI Engineer

Design, build, and operate enterprise AI platforms supporting machine learning, generative AI, and advanced analytics workloads.
Engineer scalable solutions across public and private cloud environments, ensuring security, reliability, availability, and performance.
Build and automate platform capabilities that simplify onboarding, deployment, operations, and lifecycle management for AI solutions.
Develop and maintain infrastructure, tooling, and services that support model training, evaluation, deployment, monitoring, and governance.
Implement and enhance MLOps capabilities that enable repeatable, scalable, and secure AI development workflows.
Design and maintain observability solutions, including telemetry, performance monitoring, logging, alerting, operational analytics, and drift detection.
Support production AI platforms and services, proactively identifying opportunities to improve reliability, scalability, efficiency, and customer experience.
Partner with internal engineering teams to understand requirements, enable platform adoption, and accelerate delivery of AI-powered products.
Collaborate with infrastructure, security, architecture, and governance teams to ensure alignment with enterprise standards, controls, and regulatory requirements.
Evaluate emerging AI technologies, platform capabilities, and industry trends to help shape the future direction of Mastercard's AI ecosystem.
Drive automation and engineering best practices through Infrastructure as Code, CI/CD, testing, and operational excellence initiatives.
Participate in troubleshooting, root cause analysis, operational support, and incident response activities to maintain highly available platforms.
Contribute to technical design discussions, architecture reviews, and long-term platform strategy.
Mentor peers and share knowledge across engineering teams while contributing to a culture of continuous improvement.