Platform Engineer | 10+ Years' Experience

About CloudifyAI

CloudifyAI is a certified Google Cloud Partner specializing in cloud infrastructure, data modernization, and AI solutions. We help organizations accelerate cloud adoption, modernize enterprise systems, and build scalable, reliable technology platforms.

Our team works across cloud engineering, infrastructure automation, data platforms, and AI/ML solutions, collaborating with clients to solve complex technical challenges.

Why Join CloudifyAI?

This role suits engineers who enjoy solving hard infrastructure problems with modern cloud technology. You will work with large-scale Kubernetes environments, GPU computing, HPC infrastructure, and AI/ML platforms across multiple cloud providers.

Key Responsibilities

• Operate and scale production Kubernetes platforms across AWS EKS, CoreWeave CKS, and Google GKE.
• Manage cluster lifecycle, node pool configuration, and network policies while maintaining stability during rapid growth.
• Provision GPU-enabled HPC infrastructure through CI/CD across AWS, CoreWeave, GCP, and OCI, with additional providers planned.
• Write and review Terraform daily to build and maintain infrastructure as code.
• Manage GPU workload scheduling and resource allocation across training and inference workloads.
• Build Python tools to automate platform operations and workflows.
• Define and maintain SLIs and SLOs, and build monitoring and alerting.
• Participate in severity escalation and author post-incident reviews.
• Collaborate daily with Networking, Storage, Security, and AI/ML platform teams.

Required Qualifications

• 10+ years of experience in infrastructure engineering, cloud platforms, or HPC.
• 4+ years operating production Kubernetes at scale, including node pool sizing, scheduler debugging, CNI troubleshooting, and rolling upgrades across large fleets.
• Strong Terraform skills, with experience writing and reviewing infrastructure as code daily.
• Working knowledge of AWS, including EC2, S3, EFS, and FSx for Lustre.
• Proficiency in Python for tooling and automation.
• Practical experience with GPU or HPC job scheduling and resource management.

Preferred Qualifications

• Experience running Kubernetes on GCP, CoreWeave, or OCI.
• Hands-on experience managing HPC infrastructure and GPU-enabled computing workloads.
• Familiarity with GPU and batch schedulers such as Slurm, Kueue, or Volcano.
• Experience with NVIDIA GPU Operator or DCGM.
• Experience with Prometheus, Grafana, or similar observability tools.
• Strong Linux administration and networking fundamentals (DNS, TCP/IP).
• Familiarity with infrastructure security practices, including IAM, RBAC, and access controls.

Recruitment Process

This posting is for a future opportunity and is not for a current vacancy. We are building our candidate pipeline now, and applying early means you will be among the first considered when the position opens. Next steps may include technical discussions and interviews.

Equal Opportunity

CloudifyAI welcomes applications from people of all backgrounds and is committed to fair and inclusive hiring.

Applicant Privacy and AI-Assisted Screening

CloudifyAI uses AI-assisted tools to support resume screening and candidate evaluation. AI helps assess applications against job requirements, but all final hiring decisions are made by human reviewers. Applicant information will be handled in accordance with applicable privacy and data protection requirements.

Additional Information

This position is fully remote within the United States or Canada, subject to employment eligibility and applicable local requirements.

Compensation and benefits will be determined when the position is approved. Applicable salary disclosure requirements will be addressed before advertising an approved vacancy.