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Maple Leaf Sports & Entertainment Partnership (MLSE)

Operates professional sports teams and venues

Senior Software Engineer - Developer Platform

Platform EngineeringConfirmed live in the last 24 hours
Full-timeToronto, ON, CanadaNo salary listedIn-person

About the Job

Requirements

  • At least 5 years of professional software engineering experience, including designing, building, and operating production systems.
  • Strong software development skills in one or more modern programming languages such as TypeScript/JavaScript or Python, with ability to contribute to backend applications and services.
  • Strong understanding of API design, distributed systems, authentication and authorization, databases, networking, and modern application architecture.
  • Experience designing maintainable, reusable software components rather than solving problems only within a single application.
  • Strong Git and software development fundamentals, including code review, testing, dependency management, release management, and debugging.
  • Strong hands-on experience with AWS and designing, deploying, and operating cloud-native applications.
  • Experience with containers and Kubernetes, including Docker, Kubernetes/EKS, Helm, ingress, configuration, secrets, scaling, and troubleshooting.
  • Experience with Infrastructure as Code and automated infrastructure provisioning using Terraform, CloudFormation, CDK, or equivalent.
  • Experience designing and maintaining shared platform capabilities reusable across multiple applications and development teams.
  • Strong understanding of cloud networking, identity and access management, secrets management, observability, reliability, and production operations.
  • Ability to evaluate infrastructure and application architectures for security, scalability, reliability, performance, and cost.
  • Strong experience designing and maintaining CI/CD pipelines, preferably using GitHub Actions or comparable tooling.
  • Experience creating reusable build, test, deployment, and release workflows across multiple repositories or applications.
  • Experience building developer tooling, application templates, reusable libraries, software development kits, command-line interfaces, or internal platforms that reduce repetitive engineering work.
  • Ability to identify recurring development and operational tasks and turn them into automation, self-service capabilities, and paved-road patterns.
  • Strong understanding of developer experience and ability to balance standardization and guardrails with developer flexibility.
  • Working knowledge of secure software development practices, including identity and access management, secrets, dependency management, application security, network security, and least-privilege access.
  • Experience working with Infrastructure, Cybersecurity, or other technical governance functions to move applications through architecture, security, and production-readiness reviews.
  • Ability to translate security and infrastructure requirements into practical tooling and automated guardrails rather than relying solely on manual review.
  • Practical experience using modern AI-assisted development tools such as Claude Code, GitHub Copilot, or Codex as part of day-to-day software development.
  • Strong interest in developing approaches for integrating generative AI into the software development lifecycle, including development, testing, code review, documentation, security, and operational workflows.
  • Ability to evaluate where AI and agentic workflows provide value and where traditional deterministic software, automation, or reusable libraries are more appropriate.
  • Interest in building tooling and standards that allow traditional engineers and AI-enabled or non-traditional developers to build software quickly and reliably.
  • Understanding of model usage, token consumption, observability, and cost management as AI becomes a larger component of software development and production systems.
  • Ability to take broad technical problems from discovery through prototype, implementation, productionization, and ongoing operation.
  • Strong technical judgment and ability to independently make implementation decisions within established architectural standards.
  • Ability to review application and infrastructure designs, identify risks, and recommend practical solutions before formal Architecture, Infrastructure, or Cybersecurity review.
  • Comfort working across application development, infrastructure, architecture, security, and operations rather than within a narrowly defined technical domain.
  • Strong communication skills and ability to work directly with software engineers, architects, infrastructure and security teams, product teams, and other technical stakeholders.

Responsibilities

  • Build production software while improving the platforms, tools, and practices that enable other developers to work effectively.
  • Design, build, and operate production systems and cloud-native applications.
  • Design and maintain shared platform capabilities and reusable workflows across applications, repositories, and development teams.
  • Create developer tooling, automation, self-service capabilities, and paved-road patterns to reduce repetitive engineering work.
  • Work with technical governance functions to progress applications through architecture, security, and production-readiness reviews.
  • Integrate generative AI into software development workflows where appropriate and develop tooling and standards for reliable software delivery.
  • Review application and infrastructure designs, identify risks, and recommend practical solutions.
  • Enable other engineers by making effective software development and deployment practices easy to follow.

Desired Qualifications

  • Experience building or operating an internal developer platform or Platform Engineering capability.
  • Experience with AWS services including EKS, RDS, S3, DynamoDB, Lambda, IAM, CloudWatch, Route 53, and WAF.
  • Experience with OAuth 2.0, OIDC, enterprise identity providers, and application authorization patterns.
  • Experience with AI platforms or model providers such as Amazon Bedrock, Anthropic, or OpenAI.
  • Experience implementing cloud FinOps, cost attribution, infrastructure optimization, or AI/model usage monitoring.
  • Experience modernizing existing applications, development practices, or CI/CD environments.
  • Experience supporting products that integrate with external APIs, SaaS platforms, data systems, or enterprise services.
  • Experience working in an environment where rapid prototyping must coexist with production security, reliability, and operational standards.

About the Company

Maple Leaf Sports & Entertainment Partnership (MLSE)

Operates professional sports teams and venues

MLSE owns and operates multiple professional sports teams in Toronto (Maple Leafs, Raptors, Toronto FC, Argonauts) and manages major venues (Scotiabank Arena, BMO Field, Coca-Cola Coliseum). It generates revenue from ticket sales, broadcasting rights, sponsorships, merchandise, and premium hospitality across its teams and venues. The company runs these franchises and venues as an integrated platform, focusing on fan engagement and digital content to maximize value. Its differentiator is the combination of a diversified portfolio of sports franchises and world-class venues in one regional hub, enabling cross-promotions, premium experiences, and cohesive brand growth. The goal is to maximize franchise and venue value, grow fan engagement, and ensure financial stability through multiple revenue streams and community involvement.

Company size
1,001-5,000
Company stage
Private
Total funding
$400M
Headquarters
Toronto, Canada
Founded
1931

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