About the role#
The AI Platform Engineering team builds artificial intelligence solutions for internal business teams. As a Forward Deployed Engineer Intern, you will join discovery sessions to learn how operational workflows function. You will help design, build, and deploy AI agents, tools, and intelligent workflows on our enterprise agentic AI platform. Working alongside senior engineers, you will contribute to scoped solutions from prototype through pilot, translate business needs into technical designs, and bring field feedback back to the platform team.
What you'll do#
- Build and deploy AI agents, tools, and intelligent workflows for specific business use cases.
- Integrate agents with enterprise data sources, internal APIs, and business systems using Python or TypeScript.
- Apply retrieval-augmented generation (RAG), tool and function calling, and multi-step orchestration patterns.
- Join discovery sessions with business teams to document workflows, pain points, and requirements.
- Support demos and pilot rollouts, gather user feedback, and track adoption metrics.
- Create enablement materials such as quick-start guides, demos, and FAQs.
- Write evaluation cases and test datasets.
- Use observability and tracing tools to investigate failures.
- Contribute to guardrails, error handling, documentation, and runbooks.
What you'll need#
- Currently pursuing a bachelor's or master's degree in Computer Science, Engineering, Data Science, or a related field.
- At least one term of study remaining or graduating within the internship window.
- Hands-on experience building software that integrates LLMs, machine learning models, or AI services via academic projects, co-ops, internships, hackathons, or personal projects.
- Working proficiency in Python or TypeScript.
- Comfort with REST or GraphQL APIs, JSON, and Git-based workflows.
- Foundational familiarity with LLM application patterns like prompt design, RAG, tool calling, and agentic orchestration frameworks (e.g., LangChain, LangGraph, or OpenAI Agents SDK).
- Exposure to cloud environments, preferably AWS services such as Bedrock, Lambda, and DynamoDB.
- Exposure to containerization with Docker.
- Ability to ask clear questions of non-technical stakeholders, demo working software, and write clear documentation.
- Preferred: familiarity with LLM evaluation frameworks, AI observability tooling, vector databases, or front-end development with React or Next.js.
Location & details#
- Location: Toronto, Ontario, Canada.
- Work Modality: Hybrid.
- Employment Type: Full-time.
- Term: Rolling (8-12 months).
- Compensation: $54,400 - $74,800 annually.
- Note: Applicants must be legally authorized to work in Canada. Sponsorship is not provided.
About Element Fleet Management
Element Fleet Management provides fleet management services for clients across the globe. Founded in 1946, the firm offers vehicle leasing, maintenance, and fuel expense management. It also assists with fleet electrification and risk management. The company operates as a public entity with a workforce of 1,001 to 5,000 employees based out of Toronto, Ontario.
How to get in at Element Fleet Management
Applying early is a significant advantage when pursuing a role at Element Fleet Management, as recruiters often review candidates before the applicant pool becomes unmanageable. Intern Insider sends an instant alert the moment a role matching your target is published, ensuring you can submit your materials among the first. This timing helps your application stand out before the pile grows. You should also consider reaching out to the recruiters behind the company's roles to ask about the position or a potential referral. Intern Insider surfaces these specific contacts, which can materially improve your response rates compared to submitting through a general portal. Connecting directly with a human who understands the team's needs is a practical way to show genuine interest in the work.
