Principal 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 Principal AI Engineer Overview: Mastercard is seeking a Principal AI Engineer to design and deliver enterprise-scale AI platform capabilities that help teams build, deploy, evaluate, and operate AI-powered applications securely and reliably. This role combines deep software engineering expertise with platform engineering and cloud architecture experience. You will operate as a hands-on technical leader responsible for designing scalable AI systems, defining platform standards, and driving implementation across application, infrastructure, and operational domains. Role: • Design scalable architectures for AI applications, distributed services, APIs, event-driven workflows, and data-intensive workloads. • Build production-grade backend services, orchestration frameworks, and reusable platform components. • Define platform patterns, reference architectures, and implementation standards that accelerate enterprise AI adoption. • Translate ambiguous business and product requirements into secure, scalable technical solutions that can pass architecture, governance, and security review. • Drive architectural decisions across service boundaries, data flows, performance, extensibility, reliability, and security. • Design and evolve cloud-native foundations, including Kubernetes, containers, networking, deployment automation, and infrastructure as code. • Establish standards for observability, SLOs, deployment and rollback, capacity planning, resiliency, and disaster recovery. • Produce architecture diagrams, flowcharts, and design documentation, and lead architecture, security, and governance reviews. • Contribute hands-on through development, code reviews, design reviews, and technical coaching. • Evaluate emerging AI, cloud, and platform technologies and guide practical adoption decisions. All About You: • Strong engineering experience designing, delivering, and operating large-scale production systems. • Proven ownership of complex platform, infrastructure, or enterprise software solutions from design through production. • Experience leading technical initiatives across multiple teams and influencing architecture decisions at scale. • Hands-on experience with Python and modern backend technologies. • Experience designing APIs, distributed systems, event-driven architectures, and cloud-native applications. • Strong understanding of software design principles, testing strategies, CI/CD, and continuous delivery practices. • Deep experience operating systems on AWS, Azure, or GCP, with hands-on Kubernetes, containers, and cloud-native architecture experience. • Experience with infrastructure as code tools such as Terraform, CloudFormation, Helm, or similar technologies. • Understanding of modern GenAI application patterns, including RAG, evaluation frameworks, prompt engineering, AI observability, model lifecycle management, and agents or agent orchestration. • Strong knowledge of networking, identity, security, reliability, monitoring, incident management, and operational readiness practices. • Ability to present, promote, defend, and demonstrate technical solutions to engineers, architects, product leaders, security partners, governance bodies, and executive stakeholders. • Track record of mentoring teams and driving technical excellence across an organization. Preferred: • Experience building enterprise AI platforms, GenAI solutions, or developer platforms. •