Inworld AI

Staff Platform Engineer

Inworld AI

full-time

Posted on:

Location Type: Hybrid

Location: Vancouver • 🇨🇦 Canada

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Salary

💰 CA$150,000 - CA$240,000 per year

Job Level

Lead

Tech Stack

AnsibleAzureCloudGoGoogle Cloud PlatformKubernetesOraclePythonTerraform

About the role

  • Work closely with backend and ML engineering teams to design, deploy, and maintain reliable, high-performance, and secure cloud infrastructure for our AI engine and Studio.
  • Facilitate a "you build it, you run it" culture by providing the necessary tools and processes for monitoring the reliability, availability, and performance of services.
  • Manage CI/CD pipelines to ensure smooth and efficient code integration and deployment.
  • Identify and implement opportunities to enhance engineering speed and efficiency.
  • Conduct root cause analysis to identify critical issues and develop automated solutions to prevent recurrence.
  • Develop and share best practices to improve automation and efficiency across our engineering teams.

Requirements

  • 7 years of experience in software engineering.
  • 5 years of experience with infrastructure-as-code.
  • Proficiency in managing Kubernetes clusters and applications, including creating Kustomize manifests/Helm charts for new applications.
  • Experience in creating and maintaining CI/CD pipelines for both applications and infrastructure deployments (using tools like Terraform/Terragrunt, ArgoCD, GitHub Actions, Ansible, etc.).
  • Deep knowledge of at least one major cloud provider (Google Cloud Platform, Microsoft Azure, Oracle Cloud).
  • Proficient in at least one backend programming/scripting languages such as Golang, Python, and Bash.
  • Experience with GPUs (optional).
  • Experience with MLOps (huge plus!)

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
software engineeringinfrastructure-as-codeKubernetesCI/CD pipelinesTerraformArgoCDGitHub ActionsAnsibleGolangPython
Soft skills
collaborationproblem-solvingautomationefficiency improvementroot cause analysisbest practices development