AI Cloud & Infrastructure Engineer
Toronto, Ontario, Canada
Contract
Job Description
Proven hands-on experience building AI systems and infrastructure ,
- LLM gateways
- MCP servers and MCP-Context-Forge
- Multi-agent workflows and orchestration frameworks
- Conversational / agentic AI pipelines
Strong software engineering fundamentals:
- 100% coding in Python — ability to design and build frameworks, APIs, or developer platforms
- Deep knowledge of packaging, testing, versioning, and CI/CD for Python
- Experience with RAG patterns and retrieval pipelines
- Semantic Kernel experience is a strong asset
Cloud, Containers & Kubernetes:
- Expert understanding of Docker, containers, and Kubernetes
- Experience deploying containers and managing enterprise-grade K8s environments
- Understanding of unified network security and observability in Kubernetes
GenAI & MLOps Knowledge:
- Familiarity with model serving, workflow orchestration, and multi-agent systems
- Understanding of responsible AI, compliance, and regulated-industry constraints
- Emphasis on custom development rather than simply spinning up infrastructure