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 opportunity?
• 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. Significant 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