Opens LinkedIn
- Employment type
- Contract
- Experience level
- Mid-level · 2+ years
- Posting language
- English
- Working hours
- 40 hours per week
- Location requirements
- Country, Toronto, Ontario, Canada
- Seniority
- Mid-Senior level
- Application method
- Apply on LinkedIn (LinkedIn sign-in required)
Job summary
Operate and scale Kubernetes platforms and HPC infrastructure across AWS, CoreWeave, GCP, OCI, and other cloud providers, including cluster lifecycle, node pools, networking, and GPU job scheduling. Maintain reliability through monitoring, alerting, incident response, SLI/SLO management, and coordination with networking, storage, security, and AI/ML teams.
Job details
Lead Cloud Platform Engineer/ Kubernetes Platform Engineer Toronto, ON (Remote/ Hybrid) Must be able to travel to customer location occasionally Contract Job Description: AWS customer develops and manages several HPC clusters across AWS, CoreWeave, GCP, and other providers. Several thousand GPUs today, scaling to 10X in 2026 and beyond. This role is Kubernetes heavy. You'll operate multi cloud platform infrastructure where misconfigurations or failed upgrades translate directly into thousands of lost GPU hours. The clusters are large enough that novel failure modes are routine. Responsibilities Operate Kubernetes platforms (EKS, CKS, GKE) at significant scale across providers. You're responsible for cluster lifecycle, node pool management, networking policy, and maintaining stability during rapid growth. Provision HPC infrastructure through CI/CD system across AWS, CoreWeave, GCP, and OCI, with additional providers to be expanded in the near future. Manage job scheduling to allocate GPU compute across training and inference workloads. Define and maintain SLIs/SLOs. Build monitoring and alerting. Participate in severity escalation response and author post incident reviews. Coordinate daily with Networking, Storage, Security, and AI/ML platform teams. Requirements 4+ years in infrastructure engineering, cloud platforms, or HPC. Kubernetes is the core requirement. You should have hands on experience operating clusters at meaningful scale: node pool sizing, scheduler debugging, CNI troubleshooting, and rolling upgrades across large fleets. Candidates whose K8s experience is limited to small or local environments are unlikely to be a fit. Terraform proficiency. You'll write and review infrastructure as code daily. Working knowledge of AWS (EC2, S3, EFS, FSx for Lustre). Python for tooling and automation. Other information Remote US / CAN Must be able to travel to customer location occasionally Role is long term 1yr plus Need 10+ resources with this profile.Â
What you’ll do
Operate and scale Kubernetes platforms and HPC infrastructure across AWS, CoreWeave, GCP, OCI, and other cloud providers, including cluster lifecycle, node pools, networking, and GPU job scheduling. Maintain reliability through monitoring, alerting, incident response, SLI/SLO management, and coordination with networking, storage, security, and AI/ML teams.
Requirements
Requires at least four years of infrastructure, cloud platform, or HPC experience, with hands-on experience operating Kubernetes clusters at significant scale, including node pool sizing, scheduler debugging, CNI troubleshooting, and rolling upgrades. Also requires Terraform proficiency, working knowledge of AWS services such as EC2, S3, EFS, and FSx for Lustre, and Python for tooling and automation.
Listed skills
- Kubernetes · Preferred
- CI/CD · Preferred
- Amazon Web Services · Preferred
- Terraform · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Kubernetes
- Amazon EKS
- CKS
- Google Kubernetes Engine
- Terraform
- AWS
- Python
- High-Performance Computing
- GPU Infrastructure
- Cluster Lifecycle Management
- Node Pool Management
- Kubernetes Scheduling
- Container Networking
- CI/CD
- Monitoring and Alerting
- Service-Level Indicators and Objectives
Job areas
- Technology
- Software
- Engineering
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