Overview:

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.

What you will do:  

Platform strategy and engineering 

• 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 

CI/CD and platform automation 

• 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. 

Observability and reliability

• Establish end-to-end observability practices across the platform using Datadog.
• Implement monitoring, logging, tracing, and reliability practices to ensure highly resilient platform services.

AI platform enablement

• 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.

Platform product management

• 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.

Developer experience and engineering enablement

• 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.

Leadership and collaboration

• 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.

Required Technical Qualifications: 

• 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.

What makes you successful in this role

• 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.

Preferred Qualifications: 

• 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.

What We Offer:  

The annual base salary range for this position is $175,000 - $200,000. Additionally, this position is eligible for an annual discretionary bonus based on performance.

You will also be eligible for the following benefits:

• Paid Time Off 
• Comprehensive benefits plan 
• Company RRSP Match 
• Development opportunities through the LinkedIn Learning platform 

Guidepoint powers end-to-end research workflows for the world’s best research teams.

Backed by a global network of more than 2 million experts and over 1,600 employees, Guidepoint delivers real-time access to expertise, primary research, and actionable knowledge that help organizations make informed decisions. Through consultations, surveys, events, proprietary content, and AI-enabled tools, we support every stage of the decision-making process—from developing hypotheses and gathering insights to validating assumptions and building conviction for critical decisions.

At Guidepoint, our success relies on the diversity of our employees, experts, and clients, which enables us to foster meaningful connections and a broad range of perspectives. We are committed to creating an inclusive and welcoming environment where individuals of all backgrounds, identities, and experiences can contribute and succeed.

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