Principal Platform Engineer

Guidepoint•Toronto, ON

7d•CA$175,000 - CA$200,000•Hybrid

About The Position

We are building a modern internal platform that enables application, data, and AI teams to build, deploy, and scale software efficiently and securely. We are looking for an experienced Principal Platform Engineer to drive the development of our Internal Developer Platform (IDP). The ideal candidate started their career as a software engineer, later transitioned into platform engineering, and has grown into a technical leader capable of guiding teams and building scalable platforms. This role combines hands-on engineering with leadership, ensuring the platform delivers a great developer experience while maintaining reliability, governance, and scalability. You will provide guidance and mentorship to a team of platform engineers while working closely with application teams, data teams, cloud operations, and security teams to enable modern cloud-native, Data and AI workloads. This is a hybrid position based in our Toronto office.

Requirements

Five or more years of experience as a software developer, followed by experience in platform engineering.
Proven experience designing and operating Kubernetes-based platforms in production environments.
Experience building or contributing to Internal Developer Platforms (IDP).
Hands-on experience with Argo CD, KEDA, Backstage, and Kyverno.
Strong experience building CI/CD pipelines for modern and legacy applications.
Deep experience implementing observability solutions using Datadog.
Strong knowledge of cloud-native architectures and container platforms.
Experience with infrastructure as code tools such as Terraform
Experience mentoring platform engineering teams.
You think in terms of platforms and developer experience, not just infrastructure.
You bring a product mindset to platform engineering.
You enjoy building systems that enable other engineers to move faster.
You balance hands-on engineering with leadership responsibilities.
You are highly collaborative and enjoy coaching engineers and teams.

Nice To Haves

Experience supporting AI/ML, Data platforms or model deployment infrastructure.
Experience managing multi-cluster Kubernetes environments.
Experience with service meshes such as Istio or Kong
Experience building large-scale self-service engineering platforms.
Contributions to open-source cloud-native or Kubernetes projects.

Responsibilities

Lead the design and evolution of a scalable Internal Developer Platform (IDP) that enables self-service infrastructure and developer productivity.
Architect and operate production-grade Kubernetes platforms supporting microservices, data workloads, and AI/ML systems.
Implement GitOps-based deployment workflows using Argo CD.
Build and maintain developer portals using Backstage to streamline service onboarding and platform access.
Implement event-driven autoscaling using KEDA for scalable workloads.
Enforce platform governance through policy-as-code using Kyverno.
Build reusable platform components, templates, and golden paths that simplify development workflows.
Manage and maintain all platform tools
Design and standardize CI/CD pipelines for both modern cloud-native applications and legacy development environments.
Implement GitOps and infrastructure-as-code practices to ensure consistent, automated platform operations.
Enable engineering teams with self-service deployment and infrastructure capabilities.
Establish end-to-end observability practices across the platform using Datadog.
Implement monitoring, logging, tracing, and reliability practices to ensure highly resilient platform services.
Build platform capabilities that support AI/ML experimentation, model training, and inference workloads.
Collaborate with data scientists and ML engineers to enable scalable and reliable AI infrastructure.
Operate the platform with a platform-as-a-product mindset, continuously improving capabilities based on developer needs and feedback.
Define and maintain platform roadmaps, standards, and service offerings that align with engineering and business goals.
Measure and improve developer productivity and platform adoption metrics.
Champion developer experience across the organization by simplifying development, deployment, and operational workflows.
Provide documentation, training, and onboarding support to help teams adopt platform capabilities effectively.
Create standardized golden paths that guide teams toward best practices.
Mentor a team of platform engineers.
Provide technical guidance, architectural direction, and hands-on support when needed.
Foster a highly collaborative engineering culture focused on reliability and developer productivity.
Work closely with application engineering, data engineering, cloud operations, and security teams to align platform capabilities with organizational needs.
Coach engineering teams on platform adoption and modern cloud-native practices.