Senior DevOps/Platform Engineer Job Listing at Mastercard in Toronto, ON (Job ID R-272108)

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

Senior DevOps/Platform Engineer Overview:
Mastercard powers economies and empowers people across 200+ countries and territories. Together with our customers, we build a sustainable, inclusive economy by enabling secure, simple, smart, and accessible digital payments. Our technology, innovation, partnerships, and networks deliver products and services that help people, businesses, and governments reach their full potential.

We are seeking a Senior DevOps/Platform Engineer to join the Mastercard Foundry R&D team. You will help build and scale AI/ML infrastructure to support our innovation efforts, with a focus on automation, observability, and developer experience. The ideal candidate is hands-on, curious, motivated, and comfortable working in fast-moving R&D environments.

The Role:
• Drive Platform Infrastructure: Own DevOps and infrastructure for traditional cloud native applications and agentic AI systems, establishing reusable patterns for CI/CD, scalable inference, orchestration, observability, and cost control. Design secure, scalable, repeatable systems using Infrastructure as Code (IaC) to support R&D workloads.
• Build secure CI/CD & automation systems: Enable secure tool access, workload isolation, and infrastructure for LLM-backed APIs and MCP servers, while partnering with security and compliance on access control, infrastructure governance, and auditability.
• Ensure Reliability & Observability: Implement and run monitoring, logging, and alerting. Tune observability for ML-specific workloads to ensure performance, reliability, and operational insight.
• Provide Technical Leadership: Offer hands-on leadership across DevOps and platform initiatives. Review code, enforce best practices, improve tooling, and promote clean, well-tested infrastructure.
• Cross-Functional Collaboration: Partner with ML, software, and platform engineers to design deployment strategies, scope work, manage agile deliverables, and meet milestones.

All About You:
• Expertise DevOps, SRE, or platform engineering with senior/lead responsibility. Proven ability to design and operate scalable, high performance production infrastructure, especially for AI/ML workloads. Strong leadership, mentorship, and ability to translate ambiguous goals into clear technical plans.
• Deep professionalism with cloud platforms—Azure preferred (AWS/GCP also valued). Strong experience with cloud native services, serverless architectures, and managed Kubernetes (AKS/EKS/GKE). Solid understanding of Linux internals, networking, security, compliance, access controls, and mTLS.
• Expert in Terraform and Terragrunt with strong GitOps and configuration management skills. Skilled at building maintainable, automated, self-service platform capabilities and internal developer platforms.
• Advanced Kubernetes and Docker experience, including cluster operations at scale, container security, networking, and optimizing workflows for ML development.
• Familiarity with ML workflows: feature stores, model registries, AI agents, RAG architectures, and frameworks like LangChain and LlamaIndex.
• Experience with Databricks (workspace admin, clusters, Unity Catalog, Delta Lake, MLflow) and ML platforms such as Azure ML or SageMaker.
• Hands on experience with Jenkins, GitHub Actions, GitLab CI, and modern pipeline/Artifact management. Strong software engineering fundamentals with advanced Python/Bash; Go is a plus.
• Expertise with Prometheus, Grafana, ELK, and Splunk. Ability to build dashboards, alerts, and ML focused observability.
• Knowledge of secure cloud/MLOps practices, data privacy, encryption, and enterprise networking. Experience operating in highly regulated environments.
• Strong communication and documentation skills. Comfortable working cross functionally and delivering iteratively in an Agile environment.
• Databricks Lakehouse expertise, ML frameworks (TensorFlow, PyTorch, Scikit learn), contribution to open-source, cloud/AI certifications, and enthusiasm for emerging technologies in AI and cloud-native systems.


#AI1 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 reasonable_accommodation@mastercard.com 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

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• 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: $111,000 - $160,000 CAD

 Apply on company website