Principal AI Engineer

Mastercard
Toronto
Workplace: OnsiteFull timeCAD 138,000 - 221,000 annuallyFunction: Data Science & Machine LearningSkills: ["Hands-on leadership","Technical coaching","Mentoring","Stakeholder communication"]

Design and deliver enterprise-scale AI platform capabilities that enable teams to build, deploy, evaluate, and operate AI-powered applications securely and reliably. Lead hands-on architecture across distributed services, APIs, event-driven workflows, and data-intensive workloads. Build reusable backend services and cloud-native foundations (e.g., Kubernetes, containers, IaC), establish observability/SLO standards, and guide governance, security reviews, and adoption of emerging AI and platform technologies.

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FursaFursa
Mastercard
Mastercard
1 month ago

Principal AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Status: Live
Reposted: similar role first listed 5 months ago

Job Summary

Design and deliver enterprise-scale AI platform capabilities that enable teams to build, deploy, evaluate, and operate AI-powered applications securely and reliably. Lead hands-on architecture across distributed services, APIs, event-driven workflows, and data-intensive workloads. Build reusable backend services and cloud-native foundations (e.g., Kubernetes, containers, IaC), establish observability/SLO standards, and guide governance, security reviews, and adoption of emerging AI and platform technologies.
Location: Toronto
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design scalable architectures for AI applications, including 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 to accelerate enterprise AI adoption.
  • •Design and evolve cloud-native foundations (Kubernetes, containers, networking, deployment automation, and infrastructure as code).
  • •Lead observability, SLOs, deployment/rollback, capacity planning, resiliency, disaster recovery, and architecture/security/governance reviews.

Pay and Benefits

Salary: CAD 138,000 - 221,000 annually

Key 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.
  • •Hands-on experience with Python and modern backend technologies.
  • •Experience designing APIs, distributed systems, event-driven architectures, and cloud-native applications.
  • •Deep experience with AWS, Azure, or GCP, including hands-on Kubernetes and containers, plus infrastructure-as-code tools (e.g., Terraform, CloudFormation, Helm).
Experience:AI platformsGenAICloud-nativeEnterprise softwareFintechRegulated environments
Skills:Hands-on leadershipTechnical coachingMentoringStakeholder communication
Tech Stack:PythonAPIsDistributed systemsEvent-driven architecturesKubernetesContainersAWSAzureGCPCloud-nativeInfrastructure as codeTerraformCloudFormationHelmCI/CDContinuous deliveryRAGPrompt engineeringAI observabilityModel lifecycle management

Company Brief

Mastercard
Mastercard is a global payments and technology company that processes transactions, provides fraud prevention and data services, and builds payment infrastructure for consumers, businesses, merchants and governments across 200+ countries.
Industry: Payments
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Purchase, New York, United States
Founded: 1966
Glassdoor
Glassdoor: 4.1
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