Get started on an exciting career at Element

Element employees make a difference in the lives of others every day. We are re-defining the fleet management industry to be people first, then business – delivering on our promise of a superior client experience. This takes hard work and innovation, and we need more like-minded people on our team.

Build and deploy practical AI solutions from business problem to working pilot.

THE OPPORTUNITY

The AI Platform Engineering team brings artificial intelligence solutions directly to the business teams it serves. As a Forward Deployed Engineer (FDE) Intern, you will join discovery conversations, learn how operational workflows work, and help design, build, and deploy AI agents, tools, and intelligent workflows on Element's enterprise agentic AI platform. Working alongside senior engineers, you will contribute scoped solutions from prototype through pilot, translate business needs into technical designs, and bring field feedback back to the platform team. You will receive structured mentorship, clearly scoped ownership, and regular feedback while gaining hands‑on exposure to production AI delivery.

What You Will Own

- Build and deploy AI agents, tools, and intelligent workflows on Element's agentic AI platform for scoped business use cases, with guidance from senior engineers.
- Integrate agents with enterprise data sources, internal APIs, and business systems using Python and/or TypeScript within platform governance, security, and permission boundaries.
- Apply retrieval-augmented generation (RAG), tool and function calling, and multi-step orchestration patterns using established platform patterns and templates.
- Join discovery sessions with internal business teams, document workflows and pain points,



and help translate needs into use‑case specifications, agent designs, and acceptance criteria.
- Support demos and pilot rollouts, gather user feedback, track adoption and outcome metrics, and create lightweight enablement materials such as quick‑start guides, demos, and FAQs.
- Write evaluation cases and test datasets, use observability and tracing tools to investigate failures, and contribute to guardrails, fallbacks, error handling, documentation, and runbooks.

You Should Consider This Role If

You are curious, comfortable with ambiguity, and eager to move between coding and collaboration with business users.

- You are currently pursuing a bachelor's or master's degree in Computer Science, Engineering, Data Science, or a related field, with at least one term of study remaining or graduating within the internship window.
- You have hands‑on experience through academic projects, co‑ops, internships, hackathons, or personal projects building software that integrates large language models, machine learning models, or AI services.
- You have working proficiency in Python and/or TypeScript and are comfortable with REST or GraphQL APIs, JSON, and Git‑based workflows.
- You have foundational familiarity with LLM application patterns such as prompt design, retrieval‑augmented generation (RAG), tool or function calling,



and agentic orchestration frameworks such as LangChain/LangGraph, Strands, OpenAI Agents SDK, or similar.
- You have some exposure to cloud environments, preferably AWS services such as Bedrock, Lambda, and DynamoDB, and to containerization with Docker.
- You can ask clear questions of non‑technical stakeholders, demo working software, and write clear documentation.

Preferred experience includes familiarity with LLM evaluation frameworks, AI observability tooling, vector databases, or front‑end development with React/Next.js.

YOU SHOULD BE ABLE TO TELL US

- About an AI or software project you built, including the problem you were solving, the technical approach you chose, and what you learned from the result.
- How you have used Python and/or TypeScript, APIs, or cloud services to connect systems, data, models, or user‑facing functionality.
- How you have tested, evaluated, debugged, or improved an AI‑enabled application or workflow based on observed behaviour or user feedback.
- How you have explained or demonstrated technical work to a non‑technical audience and incorporated their feedback.

WHY ELEMENT

At Element Fleet Management, this internship gives you the opportunity to work on practical AI solutions that connect technology with real business workflows. You will learn alongside senior engineers, contribute to pilots used by internal business teams, and help improve the enterprise AI platform through field feedback and reusable patterns. Element's purpose is Move the world through intelligent mobility. In this role, you can contribute by helping build secure, useful AI‑enabled processes that reduce friction and manual effort.

📌 Forward Deployed Engineer (Toronto)
🏢 Element Fleet Management
📍 Toronto