Principal AI Engineer

Mastercard; Toronto; On-site; CAD 138,000 - 221,000; Full time

Job summary

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 blends deep software engineering with platform and cloud architecture, and you will lead as a hands-on technical leader responsible for scalable AI systems and platform standards.

This role requires translating business requirements into secure, scalable technical solutions,

Qualifications

• Proven ownership of complex platform, infrastructure, or enterprise software solutions.
• Experience leading technical initiatives across multiple teams.
• Hands-on experience with Python and modern backend technologies.
• Experience designing APIs, distributed systems, event-driven architectures, and cloud-native applications.
• Strong understanding of CI/CD and delivery practices.
• Deep experience with AWS, Azure, or GCP and Kubernetes.
• Infrastructure as code tools such as Terraform, CloudFormation, Helm.
• Understanding GenAI patterns including RAG and observability.

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 platform components.
• Define platform patterns, reference architectures, and implementation standards for enterprise AI adoption.
• Translate business requirements into secure, scalable technical solutions that pass architecture, governance, and security reviews.
• 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.

Skills

Python

Backend technologies

APIs design

Distributed systems

Event-driven architectures

Cloud-native applications

Kubernetes

CI/CD

Terraform/CloudFormation

Security awareness

Tools

Terraform

CloudFormation

Helm

Job description

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.


• 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.

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [e-mail] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility

• Abide by Mastercard’s security policies and practices;


• Ensure the confidentiality and integrity of the information being accessed;


• Report any suspected information security violation or breach, and


• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program. This posting reflects one or more current openings on our team.

Pay Ranges

Toronto, Canada: $138,000 - $221,000 CAD