Part Time Engineering Student Jobs in Toronto, ON

???? TripleTen is an EdTech company that designs and runs tech career learning programs for the US and Latin American markets. We've been doing it for over five years, teaching complete beginners — people with no prior tech background — through cohort-based programs built on our own platform and curriculum, developed in partnership with Nebius AI. Our team is fully remote and globally distributed, and we serve a large, active student base across both regions.

We're looking for the person who brings a Forward Deployed Engineering curriculum to life for students: hosts the group live events, reviews the work, runs the solution design and delivery reviews, and sets the technical bar for the people supporting alongside you. The curriculum is built by a team of senior authors.

This is a teaching and reviewing role. You'll be the senior technical presence students learn from week to week. You'll run group live events, give real engineering feedback on student deployment deliverables, and act as the escalation point for a team of supporting instructors who handle first-line questions. The best person for this is someone who has actually gone into client environments and carried AI deployments to production, has opinions about what a sound deployment looks like, and can tell an experienced engineer why their approach is wrong.

Your audience: Working production engineers, not career changers, with six to fifteen years in, mostly backend, with senior and staff engineers and the occasional engineering manager. They've shipped real software for years and are moving deliberately into forward-deployed AI work; some are already interviewing for FDE roles while they study. What they're missing is agentic systems and the client-facing half of delivery.

Format: Group live events, 1:1s, and workshops timed around US Eastern Time – mostly 2:00 PM to 9:00 PM ET. Estimated 10 to 15 hrs/week.

Please submit all resumes or CVs in English.

• Host live events focused on deploying AI systems inside a client's environment: discovery and scoping, agentic architecture, integration with enterprise systems, rollout, and adoption.
• Run 1:1 sessions and tech mock interviews for students working through projects.
• Review student projects against rubrics, including the client-facing side of the work: scoping decisions, demos, and how they explain a system to a non-technical stakeholder.
• Set the technical standard for a team of supporting instructors who cover questions and first-line review, and act as their escalation point.

• Fully remote work, with live sessions scheduled within US afternoon and evening hours.
• A digital office: we use modern tools (Notion, Slack, Zoom) to keep collaboration smooth.
• Professional trust and autonomy: no micromanaging.
• A diverse, international, close-knit team excited to work with you!

• 7+ years of professional engineering experience, currently working at senior level or above (Senior/Lead/Staff Engineer, Forward Deployed Engineer, Solutions Architect, or technical lead on customer-facing delivery).
• Has personally owned deployments end-to-end in real client or enterprise environments – first call through production go-live and adoption.
• Depth across the FDE spine: customer discovery and design sessions, scoping and delivery planning under ambiguity, stakeholder management without formal authority; LLM and agent systems in production (prompting, tool/function calling, orchestration frameworks such as LangGraph/LangChain/CrewAI, guardrails, evals, RAG over enterprise data); APIs and integrations (REST, webhooks, JSON/GraphQL), Python, and deployment on at least one major cloud.
• Can explain why an architecture or scoping decision was made, not just how it was implemented, and can diagnose and critique someone else's work live.
• Strong technical communication: translating between technical and business audiences, comfortable leading a live session, whiteboarding a solution, and writing clear, specific review feedback.
• Strong English C1+ — instruction and review are in English for a US-based audience.
• Comfortable using AI tools in day-to-day technical work.

Preferred experience:

• Has taught, mentored, or run technical sessions before: internal tech talks, onboarding, mentoring engineers, bootcamp or workshop instruction.
• Has worked embedded within a customer team as their primary technical resource, or held a customer-facing engineering role (solutions engineer, solutions architect, technical consultant).
• Production experience with agentic frameworks (LangGraph, LangChain, CrewAI) and MCP-based tool integrations into client systems.
• Work experience at a recognizable company.
• Familiarity with online education platforms or running programs.