Junior AI Developer

📍 About Arcadion

Arcadion is a leading full-stack enterprise IT services and AI development firm headquartered in Ottawa.

We specialize in delivering cutting-edge solutions across cloud infrastructure, cybersecurity, digital transformation, and AI automation.

Our AI division is at the forefront of building intelligent systems, enterprise AI agents, and next-generation tools using advanced language models (LLMs), RAG pipelines, and machine learning technologies.

We are looking for a Junior AI Developer to join our in-house team at our Ottawa headquarters.

This is a full-time, on-site position offering a unique opportunity to work directly with senior engineers and the Director of AI on innovative projects that span across sectors like healthcare, finance, construction, robotics, and legal tech.

🧪 Role Overview

As a Junior AI Developer, you’ll support the design, development, testing, and deployment of AI and machine learning applications.

You will contribute to real-world use cases involving custom LLM integrations, automation agents, document intelligence systems, and AI-enhanced enterprise tools.

🔧 Key Responsibilities

• Work closely with the Director of AI on the development of AI agents, copilots, and intelligent automation tools
• Assist in building, testing, and fine-tuning large language models and retrieval-augmented generation (RAG) pipelines
• Contribute to prompt engineering and integration of LLMs into web-based or API-driven applications
• Support data preprocessing, embedding, and vector database structuring (e.g., Pinecone, Weaviate)
• Write clean, testable Python code and support REST API integrations
• Participate in QA testing, performance benchmarking, and debugging AI system behavior
• Stay updated on emerging tools, frameworks, and trends in the AI ecosystem
• Collaborate with cross-functional teams including DevOps, cloud engineers, and UI/UX designers

✅ Requirements

• Degree or diploma in Computer Science, AI/ML, Data Science, Software Engineering, or related discipline
• Foundational knowledge in machine learning and NLP principles
• Proficiency in Python and familiarity with ML libraries like scikit-learn, PyTorch, or TensorFlow