Principal AI Engineer

Who you are

• 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
• Experience building enterprise AI platforms, GenAI solutions, or developer platforms
• Experience with AI observability and evaluation platforms
• Experience with fintech, regulated environments, or enterprise security and governance processes
• Experience supporting highly regulated or high-security environments

What the job involves

• 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
• 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