Full-Stack AI Engineer
- Toronto, ON, Canada
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Job details
- Job type
- Contract
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- Posting language
- English
- Posted
Original job description
Key Technical Must-Haves
- Full-Stack & Systems Engineering (Primary Foundation):
- Strong proficiency in TypeScript, JavaScript, Node.js, Python, React, and FastAPI/REST APIs/WebSockets.
- Robust distributed systems foundation: event-driven architectures, job queues (Pub/Sub, Cloud Tasks, SQS), caching, backpressure handling, and rate-limit management.
- Agentic Systems & Platform Tooling:
- Hands-on experience building production multi-agent systems using LangGraph or LangChain.
- Experience with MCP (Model Context Protocol), tool calling, structured LLM outputs, real-time token streaming, and agent observability/evaluation.
More about this job
Responsibilities
Build full-stack systems and production multi-agent applications. Develop and support distributed, event-driven architectures with job queues, caching, backpressure handling, and rate-limit management.
Requirements
Requires strong proficiency in TypeScript, JavaScript, Node.js, Python, React, and FastAPI, along with experience building REST APIs and WebSockets. Requires hands-on experience with production multi-agent systems using LangGraph or LangChain, plus MCP, tool calling, structured LLM outputs, real-time token streaming, and agent observability and evaluation.
Skills
- TypeScript
- JavaScript
- Node.js
- Python
- React
- FastAPI
- REST APIs
- WebSockets
- Distributed Systems
- Event-Driven Architectures
- Job Queues
- Caching
- Backpressure Handling
- Rate-Limit Management
- LangGraph
- LangChain
Visa sponsorship
Not detected in the job text
Categories
- Software
- Technology
- Engineering
Keywords
- TypeScript
- JavaScript
- Node.js
- Python
- React
- FastAPI
- REST APIs
- WebSockets
- Distributed Systems
- Event-Driven Architectures
- Job Queues
- Pub/Sub
- Cloud Tasks
- SQS
- Caching
- Backpressure Handling
- Rate-Limit Management
- Multi-Agent Systems
- LangGraph
- LangChain
- MCP
- Model Context Protocol
- Tool Calling
- Structured LLM Outputs
- Real-Time Token Streaming
- Agent Observability
- Agent Evaluation
- Full-Stack Engineering
- Systems Engineering