Summary
✨ AI‑Generated
A technology-focused organization is seeking an experienced engineer to design and operate scalable AI and cloud platforms. The role involves infrastructure automation, container orchestration, continuous delivery, and collaboration with engineering and analytics teams.
Highlights
Opportunity to build scalable AI platforms and cloud infrastructure while collaborating with cross-functional engineering and data teams on advanced analytics solutions.
Description
Job Title: AI Platform Engineer – GCP / DevOps
Location: Toronto, ON, Canada
Work Model: Hybrid
Duration: Contract
Domain: Insurance
Job Description
We are looking for a highly skilled AI Platform Engineer with strong GCP and DevOps expertise to design, build, deploy, and maintain scalable cloud platforms supporting AI/ML and fraud detection initiatives.
The ideal candidate will have hands-on experience with Google Cloud Platform, Kubernetes, Terraform, CI/CD, cloud-native infrastructure, and AI/ML platform deployment.
The role will work closely with data scientists, ML engineers, software engineers, security teams, and architects to build reliable and secure platforms for fraud detection and risk analytics.
Key Responsibilities
Design and implement scalable AI/ML platforms on Google Cloud Platform (GCP).Build and maintain cloud infrastructure using Terraform / Infrastructure as Code.Deploy and manage containerized workloads using Kubernetes / GKE.Develop and maintain robust CI/CD pipelines for application and ML model deployment.Automate infrastructure provisioning, configuration, deployment, and operational processes.Support the deployment and operationalization of machine learning models and AI workloads.Work with ML/Data Science teams to establish reliable model development and deployment pipelines.Implement monitoring, logging, alerting, and observability across GCP environments.Apply DevSecOps practices across infrastructure and deployment pipelines.Ensure cloud platforms meet enterprise requirements for security, scalability, reliability, and performance.Troubleshoot infrastructure, deployment, networking, and production issues.Collaborate with engineering and architecture teams to establish platform standards and best practices.Optimize cloud infrastructure for performance and cost.Support environments across development, QA, staging, and production.Required Technical Skills
GCP / Cloud
Strong hands-on experience with Google Cloud PlatformGKE / KubernetesCompute EngineCloud StorageBigQueryPub/SubIAMCloud Monitoring / LoggingVPC / networkingDevOps / Platform Engineering
Strong DevOps / Platform Engineering backgroundTerraformCI/CD pipelinesGitHub Actions / GitLab CI / JenkinsDockerKubernetesHelmGitAI / ML Platform
Experience supporting AI/ML workloads in cloud environmentsML model deployment and operationalizationMLOps conceptsExperience with model serving / inference platformsFamiliarity with Python and ML frameworks is preferredExperience integrating AI/ML platforms with enterprise applicationsObservability & Security
Cloud monitoring and loggingPrometheus / Grafana or equivalentApplication and infrastructure observabilityIAM and cloud securitySecrets managementDevSecOps practicesPreferred Skills
Experience in Insurance / Financial ServicesExperience with Fraud Detection / Fraud Analytics / Risk PlatformsExperience working with regulated enterprise environmentsExperience with MLOps platformsVertex AI experiencePython scriptingArgoCD / GitOpsAnsibleService mesh technologiesExperience with API platforms and microservices
