Principal AI Engineer
Mastercard1 day ago
Toronto, CanadaStaff+
Responsibilities
- 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 enterprise AI platform components.
- Define platform patterns, reference architectures, implementation standards, and cloud-native foundations.
- Drive architectural decisions involving service boundaries, data flows, performance, extensibility, reliability, security, and operational readiness.
- Establish standards for observability, SLOs, deployment and rollback, capacity planning, resiliency, and disaster recovery.
- Lead architecture, security, and governance reviews and produce architecture diagrams, flowcharts, and design documentation.
- Contribute hands-on through development, code reviews, and design reviews while mentoring teams and influencing technical direction across the organization.
- Evaluate emerging AI, cloud, and platform technologies and guide practical adoption decisions.
Requirements
- Strong 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, APIs, distributed systems, event-driven architectures, and cloud-native applications.
- Strong understanding of software design principles, testing strategies, and continuous delivery practices.
- Deep experience with AWS, Azure, or GCP and 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 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.
- Ability to present and defend technical solutions to engineering, architecture, product, security, governance, and executive stakeholders.
- Preferred experience building enterprise AI platforms, GenAI solutions, or developer platforms; using AI observability and evaluation platforms; or working in fintech, regulated, or high-security environments.
Benefits
- Competitive base pay in Toronto, Canada of $138,000-$221,000 CAD annually.
- May be eligible for a discretionary annual incentive program.
- Mastercard is an inclusive equal opportunity employer and provides reasonable accommodations during the application and recruitment process.
Tech Stack
Categories
About Mastercard
Mastercard builds and operates a global payments network used by banks, merchants, fintechs, and governments, offering card processing, real-time payments, tokenization, and fraud/risk services. It generates revenue from transaction processing and assessment/service fees across more than 200 countries and territories. Founded in 1966 and headquartered in Purchase, New York, Mastercard is a public company listed on the NYSE (ticker: MA).