DevOps Engineer – AI & Automation

Job Title: Senior Cloud DevOps Engineer – AI & Automation

Toronto (hybrid)

Experience Level: 6–8 Years

Duration: 6 Months with high possibility of extension

Role Overview:

We are seeking a highly skilled and experienced Cloud DevOps Engineer with AI & Automation expertise to design, develop, and manage scalable cloud-native solutions. The ideal candidate will have strong hands-on experience across Azure, AWS, Infrastructure as Code, and LLM/GenAI integrations, along with a deep understanding of event-driven architectures and CI/CD pipelines.

Key Responsibilities: • Design, build, and maintain scalable cloud solutions across Azure and AWS platforms • Develop and deploy serverless applications using: • Azure Functions, Logic Apps • AWS Lambda, Step Functions • Implement and manage Infrastructure as Code (IaC) using Terraform and CloudFormation • Integrate Azure OpenAI Service / LLM-based GenAI solutions into enterprise applications • Build and maintain CI/CD pipelines for automated deployments and testing • Design and implement event-driven architectures using cloud-native services • Develop and consume RESTful APIs for system integration • Monitor, troubleshoot, and optimize cloud environments using: • Azure Monitor • AWS CloudWatch • Manage cloud governance and compliance using: • Azure Resource Manager, Azure Policy • Containerize applications using Docker and orchestrate workloads using Kubernetes • Collaborate with cross-functional teams including developers, architects, and data engineers

Essential Skills: • Programming: Python (strong proficiency required) • Cloud Platforms: • Azure (Functions, Logic Apps, Monitor, Resource Manager, Policy, Azure OpenAI) • AWS (Lambda, Step Functions, CloudWatch, CloudFormation, Boto3) • Infrastructure as Code (IaC): Terraform, CloudFormation • DevOps & CI/CD: Pipeline design and implementation (Azure DevOps, GitHub Actions, or similar) • APIs: RESTful API development and integration • Architecture: Event-driven architecture patterns • Containers: Docker, Kubernetes • AI/ML: LLM & GenAI integration experience

Desirable Skills: • Experience with multi-cloud environments • Familiarity with microservices architecture • Knowledge of security best practices in cloud environments • Exposure to observability tools and logging frameworks • Experience in performance tuning and cost optimization