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 contemporary 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

📌 Principal AI Engineer (Toronto)
🏢 Mastercard
📍 Toronto