AI Engineer [Junior]
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
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- Posting language
- English
- Posted
Original job description
Role snapshot
- Title: AI Engineer (Junior)
- Location: Toronto, ON (hybrid, 2–3 days on-site)
- Engagement: Full-time, working on Augmented enterprise client projects
- Level: Junior (0–2 years of professional experience)
- Reports to: AI Engineering Lead
About the role
Augmented is hiring a Junior AI Engineer to help build and ship AI-powered applications for large enterprise clients in regulated industries. You will work alongside senior engineers on LLM-based features, from prototype to production, and grow quickly through hands-on delivery.
Key responsibilities
- Build and test features for LLM-powered applications, such as chat assistants, document processing and retrieval-augmented generation (RAG)
- Write clean, tested Python code for APIs, data preparation and model integrations
- Develop and refine prompts, and help build evaluation sets to measure output quality
- Integrate LLM APIs and vector databases into client applications
- Support deployment, monitoring and bug fixing in cloud environments
- Document your work and take part in code reviews, stand-ups and client demos
- Keep learning new AI tools and techniques and share what you learn with the team
Required qualifications
- Degree in Computer Science, Engineering, Mathematics or a related field, or equivalent practical experience
- 0–2 years of software or AI engineering experience (internships, co-ops and substantial projects count)
- Solid Python skills and familiarity with Git
- Hands-on exposure to LLMs through projects, coursework or hackathons (e.g. OpenAI, Anthropic or open-source models)
- Basic understanding of REST APIs, SQL and cloud concepts
- Curious, eager to learn and clear in written and spoken communication
- Legally entitled to work in Canada
Nice to have
- Experience with LangChain, LlamaIndex or similar frameworks
- Familiarity with vector databases (e.g. pgvector, Pinecone) and embeddings
- Basic ML knowledge (scikit-learn, PyTorch)
- Exposure to Docker, CI/CD or a major cloud (Azure, AWS or GCP)
- A GitHub portfolio or demo of an AI project you built
Tech stack
- Languages: Python, SQL, TypeScript (a plus)
- AI: LLM APIs (OpenAI, Anthropic, Azure OpenAI), open-source models
- Frameworks: LangChain / LlamaIndex, FastAPI
- Retrieval: vector databases, embeddings, RAG pipelines
- Cloud & DevOps: Azure or AWS, Docker, Git, CI/CD
Why Augmented
Augmented is an AI-native engineering delivery hub serving large enterprises in Life Sciences and Fintech, with teams in Toronto and the US.
- Learn fast by shipping real AI products for enterprise clients
- Mentorship from senior AI and data engineers
- Hands-on with modern AI tools and AI-native delivery practices
How to apply
Apply through this posting with your resume and a link to an AI project you built (GitHub, demo or short write-up).
Augmented is an equal opportunity employer. Accommodations are available on request at any stage of the hiring process.
More about this job
Responsibilities
Build, test, and integrate features for LLM-powered applications, including chat assistants, document processing, and retrieval-augmented generation, using Python, APIs, and vector databases. Support deployment, monitoring, troubleshooting, documentation, code reviews, and client demonstrations while learning and sharing new AI techniques.
Requirements
Applicants need a degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience, and 0–2 years of software or AI engineering experience. They should have solid Python and Git skills, hands-on exposure to LLMs, basic knowledge of REST APIs, SQL, and cloud concepts, and be legally entitled to work in Canada.
Skills
- Python
- Git
- Large Language Models
- Prompt Engineering
- Retrieval-Augmented Generation
- REST APIs
- SQL
- LLM Evaluation
- Vector Databases
- Embeddings
- FastAPI
- Cloud Deployment
- Docker
- CI/CD
- LangChain
- LlamaIndex
Visa sponsorship
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Categories
- Technology
- Software
- Engineering
- Data & Analytics
- Consulting
Keywords
- Python
- SQL
- TypeScript
- Git
- Large Language Models
- OpenAI
- Anthropic
- Azure OpenAI
- Open-Source Models
- Prompt Engineering
- LLM Evaluation
- Retrieval-Augmented Generation
- RAG Pipelines
- Vector Databases
- Embeddings
- LangChain
- LlamaIndex
- FastAPI
- REST APIs
- Scikit-Learn
- PyTorch
- Azure
- AWS
- Docker
- CI/CD
- Cloud Deployment
- Document Processing
- Chat Assistants
- Life Sciences
- Fintech