AI Engineering Advisor – Autonomous Agents and Agentic Platforms

Here is a brief overview of the tasks and responsibilities:

• Design, develop and scale agentic AI platforms for the creation, orchestration and deployment of autonomous agents (textual, multimodal and voice);
• Implement and design autonomous AI agents capable of planning, reasoning and acting in complex environments, interacting with existing systems and APIs;
• Define, maintain and evolve AI agent factories (architecture patterns, frameworks, tools and best practices) in order to accelerate and standardize development;
• Design and integrate industrializable RAG architectures within agents, ensuring knowledge management, reliability of responses, traceability and grounding;
• Integrate LLMs and specialized models (reasoning, vision, voice, embeddings) and set up advanced memory, planning and orchestration mechanisms;
• Apply sound software engineering principles and ensure the production of solutions (CI/CD, observability, performance, security and continuous improvement);
• Optimize the robustness, performance, safety and traceability of RAG agents and systems in production;
• Identify, in collaboration with customers and stakeholders, high value-added manual processes and propose agentic solutions to reduce operational burden and improve quality;
• Collaborate closely with technical teams and stakeholders to translate business needs into concrete and industrialized agentic solutions;
• Exercise influential technical leadership: guide technical choices, share best practices and act as a reference in agentic AI for teams and clients;
• Ensure an active technological watch and contribute to documentation, knowledge capitalization and the continuous evolution of agentic platforms and practices.

• Have a university degree in computer science, software engineering or related
  field (higher education in AI or data: an asset);
• Five (5) to ten (10) years of professional experience in computer science, with a strong component in software engineering.;
• Experience with recognized agentic frameworks and LLMOps (LangChain, LangGraph, LangFuse), as well as complementary frameworks such as Semantic Kernel, AutoGen, and Microsoft Agent Framework (or equivalents);
• Have a strong background in software development, mainly in Python, with good design, testing and maintenance practices;
• Demonstrate real-world experience with cloud services and distributed environments (Azure, AWS, or GCP), including deploying, operating, and securing AI solutions in production;
• Have experience in MLOps / LLMOps, including monitoring, evaluation and operation of AI systems (RAG agents and architectures) in production;
• Have hands-on experience with multi-agent systems, cooperative agents or agents oriented towards complex tasks;
• Knowledge of emerging protocols and standards for agentic systems, including MCP and A2A, and their use in distributed environments;
• Demonstrated ability to intervene from end to end, from design to industrialization of complex solutions;
• Demonstrate expertise in advanced RAG, including assessment of response quality, hallucination reduction, and source traceability;
• Expertise in agentic AI, including:
  • Designing single-agent and multi-agent architectures;
  • Autonomous agent orchestration;
  • The integration of LLMs, RAG pipelines, memory mechanisms, and dynamic tooling.
• Have a mastery of the different types of agent orchestrators and associated patterns (coordination, planning, execution, inter-agent collaboration);
• Have a very good command of REST APIs, system integration and workflow automation;
• Have a solid understanding of memory (short and long term), caching, connectors and context management in agentic systems;
• Demonstrate a strong interest in issues related to artificial cognition, autonomy, alignment and safety of AI agents;
• This position requires fluency in French and English for daily tasks, understanding documentation, and professional communication with customers, suppliers, and colleagues across Canada. Language skills in French and English are essential, both oral and written.