Job Title: Cloud Solutions Architect
Location: Hybrid – 2-3 days per week in the Toronto office
Level: Intermediate
Note: Only candidates whose experience closely matches the requirements will be contacted
About the Opportunity
Our client's AI Lab is a fast-moving, innovation-driven team leading the way in artificial intelligence. Based in Toronto and embedded in Canada's thriving AI ecosystem, they transform ambitious concepts into high-impact, real-world solutions. Their work includes intelligent automation, strategic forecasting, and platforms that streamline complex workflows and unlock business value. Join a team that values speed, creativity, and purpose—delivering AI that truly matters.
About the Role
As a Cloud Solutions Architect, you will design and implement scalable, secure, and cost-efficient cloud infrastructure supporting a multi-agent orchestrator platform and AI-driven initiatives. This hybrid contractor role involves close collaboration with frontend, backend, and AI engineering teams to provision and manage Azure and GCP resources. You will ensure seamless integration across environments and establish best practices for continuous deployment, monitoring, and reliability. Your expertise will enable the delivery of enterprise-grade AI solutions transforming procurement operations.
Key Responsibilities
- Design end-to-end cloud infrastructure for the multi-agent orchestrator platform.
- Implement release and test pipelines; manage DevOps practices.
- Provision, configure, secure, and scale resources on Google Cloud Platform (GCP) and Microsoft Azure.
- Ensure security, monitoring, and cost optimization of cloud environments.
Qualifications
- 3+ years of experience in cloud architecture and DevOps.
- Proven expertise with GCP and Microsoft Azure platforms.
- Hands-on experience deploying LLM or AI systems in cloud environments.
- Strong understanding of security best practices, monitoring, and cost optimization in cloud.
- Familiarity with common security vulnerabilities and mitigation techniques.
- Experience with Docker and Kubernetes container orchestration.
- Knowledge of microservices architecture and distributed systems.
- Familiarity with real-time applications using WebSockets or similar technologies.
