Our client is looking to add a Senior LLM Engineer to their AI team. In this role you will play a pivotal role in architecting and leading the development of multiple AI agent frameworks. This will be a 12-month hybrid contract with two days on-site in downtown Toronto.

Beyond hands-on technical contributions, you will lead AI initiatives, mentor other LLM engineers, and collaborate closely with business leaders to drive adoption. Your ability to translate complex AI solutions into business impact will be key to the success of our global AI strategy.

Key Responsibilities

• Lead and oversee the design, development, and deployment of LLM-powered AI agents.
• Set the technical direction for model selection, fine-tuning, and deployment strategies.
• Guide the team in implementing advanced AI techniques, including RAG, fine-tuning, and multi-agent collaboration.
• Collaborate with business leaders to align AI solutions with procurement objectives and demonstrate measurable impact.
• Ensure AI agents deliver high accuracy, reliability, and efficiency in real-world procurement tasks.
• Mentor and support junior and intermediate LLM engineers to elevate overall team performance.
• Communicate project progress, insights, and AI-driven recommendations to senior stakeholders through presentations and reports.

Requirements

• Master's degree in Mathematics, Physics, Computer Science, or a related field (PhD in LLM or NLP research is highly preferred).
• 5+ years of experience in LLM development, AI-driven automation, or NLP solutions.
• Proven expertise in LLM fine-tuning, retrieval-augmented generation (RAG), and model optimization.
• Proven experience with various LLM frameworks and models, including LangGraph, Hugging Face, GPT model suites, and Gemini model suites.
• Hands-on experience with vector databases, knowledge graphs, and AI orchestration tools.
• Ability to lead AI projects end-to-end, from research and prototyping to production deployment.
• Strong communication and presentation skills, with experience in explaining AI solutions to business leaders.
• Experience working in a cloud environment (GCP preferred).

Nice to Have

• Prior experience leading multi-agent AI systems.
• Knowledge of procurement, supply chain, or business automation workflows.
• Experience developing AI solutions in a large enterprise environment.