Cloud Architect/Engineer
Mindlance
About the role
Job Title:
Cloud Architect/Engineer
Location:
Toronto, ON (Hybrid)
Duration:
- Months
About the Role:
As a Cloud Architect, you’ll be responsible for designing and implementing scalable, secure, and cost-efficient cloud infrastructure to support our multi-agent orchestrator platform and AI-driven initiatives. This hybrid contractor role, based in Toronto, requires close collaboration with frontend, backend, and LLM engineering teams to provision and manage Azure and GCP resources, ensure seamless integration across environments, and establish best practices for continuous deployment and integration, monitoring, and reliability.
Your expertise will directly enable the delivery of enterprise-grade solutions powering Client’s next generation of intelligent procurement operations.
Responsibilities:
- Design the end-to-end cloud infrastructure for the orchestrator.
- Implement release and test pipelines and manage Dev Ops.
- Provision, setup, secure, and scale resources on Google Cloud Platform (GCP) and Microsoft Azure.
Requirements:
- years of cloud architecture and Dev Ops experience.
- Proven expertise in GCP and MS Azure.
- Hands-on experience deploying LLM or AI systems in cloud environments.
- Strong understanding of security, monitoring, and cost optimization in GCP and MS Azure.
- Understanding of common security vulnerabilities and mitigation techniques.
- Expertise with Docker and container orchestration tools like Kubernetes.
- Knowledge of microservices architecture and distributed systems.
- Familiarity with real-time applications using Web Sockets or similar technologies.
Equal Opportunity Employer:
Mindlance is an equal opportunity employer. We are committed to inclusive, equitable, barrier-free recruitment and selection processes, and work environment in accordance with the Accessibility for Ontarians with Disabilities Act (AODA). We will be happy to work with applicants requesting accommodation at any stage of the hiring process.
Requirements
- Proven expertise in GCP and MS Azure.
- Hands-on experience deploying LLM or AI systems in cloud environments.
- Strong understanding of security, monitoring, and cost optimization in GCP and MS Azure.
- Understanding of common security vulnerabilities and mitigation techniques.
- Expertise with Docker and container orchestration tools like Kubernetes.
- Knowledge of microservices architecture and distributed systems.
- Familiarity with real-time applications using Web Sockets or similar technologies.
Responsibilities
- Design the end-to-end cloud infrastructure for the orchestrator.
- Implement release and test pipelines and manage Dev Ops.
- Provision, setup, secure, and scale resources on Google Cloud Platform (GCP) and Microsoft Azure.
Skills
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