AI Engineer | Applied AI & LLM Applications

Location: Toronto, Canada | Experience: 1–5 years | Work model: Hybrid, 4 days in-office

We’re looking for a hands-on AI Engineer to build production AI agents, LLM-powered applications, and intelligent retrieval systems that solve real business problems.

This is an opportunity to work with a small, high-impact AI team, collaborate directly with senior investment professionals, and take ownership of AI solutions from idea to production.

What you’ll build

- AI agents and LLM-powered applications for real business workflows.
- Intelligent search and retrieval systems using RAG, vector search, embeddings, and knowledge graphs.
- AI evaluation frameworks to improve accuracy, reliability, and cost.
- APIs, data pipelines, and full-stack applications that turn prototypes into production-ready tools.

What we’re looking for

- 1–5 years of software engineering or applied AI experience.
- A degree in Computer Science, Engineering, Mathematics, Statistics, or a related technical field.
- Strong Python and SQL skills.




- Hands-on experience building applications with LLM APIs, such as agents, tool calling, retrieval, or AI automation.
- Experience shipping software, not just experimenting with prompts or models.
- Evidence of building through shipped products, internships, personal projects, open-source contributions, hackathons, or GitHub.
- Familiarity with AI coding tools such as Claude Code or Codex, with the ability to review and own the code they generate.

Why this chance?

- Work directly with senior investors and business leaders.
- Build AI solutions with tangible business impact.
- Own projects end-to-end in a growing AI team.
- Solve challenging problems at the intersection of AI, software engineering, and business.

Important location requirement The role is based in Toronto, Ontario, with in-office attendance Monday–Thursday and remote work on Fridays. Candidates must be able to meet this arrangement.

📌 Artificial Intelligence Engineer (Toronto)
🏢 Digivance Solutions
📍 Toronto