AI Engineer
$59,000–$74,000 year
On-site · Toronto, Ontario, Canada
Job Summary
AI Engineer (LLM/Agent) role focusing on building AI-powered copilots and a Revenue Assistant agent, designing context architecture around client pricing data, and embedding AI across PureFacts’ SaaS platform. Responsibilities include designing and building LLM-powered applications and AI agents for internal/client use, implementing prompt engineering and agent orchestration, developing AI automation for revenue insights, client reporting, and operational efficiency, integrating LLMs with data systems, building APIs/m services, creating RAG pipelines and semantic search with vector databases, evaluating and optimizing AI outputs, and ensuring secure, scalable deployments with responsible AI and governance. Requires experience with Python, LLM APIs, vector databases, LangChain/LlamaIndex, APIs/microservices, data processing, cloud platforms, and a track record in SaaS/fintech environments.
Required Qualifications
- 1-3 years of LLM application development experience (RAG pipelines, vector databases, agent orchestration)
- Experience with evaluation frameworks for generative AI and implementing guardrails in regulated contexts
- Familiar with agent frameworks (LangGraph or similar)
- Hands-on experience building LLM-based applications or AI agents
- Experience in SaaS, fintech, or data-driven environments is preferred
- Strong programming skills in Python (required)
- Experience with LLM APIs (OpenAI, Azure OpenAI, Anthropic, etc.)
- Prompt engineering and agent frameworks (LangChain, LlamaIndex, etc.)
- APIs and microservices architecture
- Data processing (SQL, Python data libraries)
- Familiarity with vector databases and embeddings
- Cloud platforms (AWS, Azure, GCP)
- Experience building RAG systems and multi-step agent workflows
- Tool-using agents and automation systems
- Understand LLM limitations and optimization techniques
- Evaluation methods for generative AI
- Strong problem-solving and systems thinking
- Clear communication across technical and non-technical teams
- Education in Computer Science, Engineering, Data Science, or related field
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