Job Title: Cloud Platform Engineer
Location: Toronto, Canada, Remote
Note: Candidate Must be ready to work in Pacific time Zone
Job Summary:
Cloud Platform Engineer to join our growing cloud engineering team. In this role, you will play a critical part in shaping and supporting cloud infrastructure, implementing CI/CD pipelines, and integrating modern observability tools. You'll work closely with cross-functional teams to ensure secure, scalable, and innovative cloud-native solutions that support enterprise applications, including AI/ML services.
Key Responsibilities:
- Design, build, and manage CI/CD pipelines using tools such as GitHub Actions, ArgoCD, or equivalent.
- Collaborate with development and operations teams to build a secure and scalable cloud foundation using Infrastructure as Code (IaC) with Terraform.
- Integrate AI/ML services into cloud applications to drive innovation and enhance product capabilities.
- Apply Agile methodologies to continuously deliver value in an iterative manner.
- Bring a product mindset to build solutions tailored to developer and end-user needs.
- Enhance observability by implementing logging, tracing, and monitoring tools to ensure high availability and performance of services.
Required Qualifications:
- Bachelor's degree in Computer Science, Engineering, or a related technical field.
- Hands-on experience with cloud platforms such as AWS and Azure.
- Strong understanding of CI/CD processes, pipelines, and infrastructure automation tools.
- Experience with Terraform and other IaC tools.
- Proficiency in programming languages such as Python or Node.js.
- Familiarity with monitoring and observability tools like DataDog , Prometheus , Grafana , or ELK Stack.
- Proven experience in creating self-service tools for deployments, monitoring, and system management.
- Excellent communication and collaboration skills.
Preferred Qualifications:
- Certifications in cloud technologies (e.g., AWS Solutions Architect , Azure Developer Associate).
- Experience with serverless architectures and microservices.
- Familiarity with deploying and managing AI/ML models in cloud environments.
