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This listing was closed on Aug 25, 2026.
Browse Open JobsAI Engineer Intern
Summary by AIEngineer.careers
AI Engineer Intern is a AI Engineer role (full-time). with ShyftLabs. in TORONTO, CA. Compensation shown: $31K–$46K (est.). Imported listing (source: interninsider.me). Apply on the employer's site (interninsider.me).
Imported listing (source: interninsider.me) · Apply on interninsider.me
TORONTO · CA
$31K–$46K (est.)
Full-time
JUNIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from interninsider.me
ShyftLabs is hiring an AI Engineer Intern to work on Continuum, an enterprise AI agent platform. The intern will build agent orchestration, integrate LLMs, implement guardrails, and develop evaluation pipelines. They will work with Python, RAG, vector databases, and various AI models. This is a hybrid role in Toronto.
Responsibilities
- Build and improve agent orchestration and multi-agent workflows.
- Develop agentic applications for enterprise use cases using the Continuum platform.
- Integrate and work with commercial and open-source models, including OpenAI, Anthropic, Gemini, Llama, Qwen, and Mistral.
- Implement AI guardrails to manage safety, security, access control, data privacy, and policy enforcement.
- Create evaluation pipelines to measure accuracy, groundedness, hallucination, tool usage, workflow completion, latency, and cost.
- Build persistent memory, state-management capabilities, and tool-calling functionality for long-running workflows.
- Design context-engineering and retrieval pipelines using vector and graph databases.
- Write clean, reusable, and documented Python code while contributing to the Continuum open-source codebase.
Requirements
ShyftLabs
Toronto · CA · 177+ employees
ShyftLabs is a business consulting and technology services company that provides AI solutions, digital transformation, and expert technology consulting. They specialize in building enterprise-grade AI systems, data infrastructure, and analytics platforms to drive measurable operational outcomes.
