Compétences recherchées — Connectez-vous et téléversez votre CV pour comparer avec votre profil
Détails du poste
- Lieu de travail : Montreal
- Type de poste : Permanent à temps plein
Description du poste
Role Summary
- Design and build intelligent agent-based systems that can reason, plan, and act autonomously.
- Strong Python engineering expertise and hands-on experience with modern agent frameworks.
- Solid understanding of data platforms and scalable architectures.
Agent & AI System Development
- Design and build agent-based systems using frameworks such as LangChain, LangGraph, or similar.
- Develop intelligent components capable of reasoning, planning, and executing tasks autonomously.
- Implement advanced cognitive patterns such as ReAct (Reasoning + Acting).
LLM Capabilities & Enhancements
- Develop and integrate memory, tool usage, and context management capabilities (MCP).
- Build systems that leverage tool calling, chaining, and orchestration of LLM workflows.
- Collaborate with prompt engineers to enhance model responses and performance.
Engineering & Development
- Write high-quality, scalable code using Python, including async programming.
- Build and maintain APIs and microservices for AI/agent-based applications.
- Ensure systems are efficient, reliable, and production-ready.
Guardrails & Responsible AI
- Design and implement guardrails and safety mechanisms for LLM-driven systems.
- Ensure robust handling of edge cases, failure scenarios, and unintended outputs.
Data & Platform Integration, Work with modern data platforms such as:
- Snowflake
- Databricks
- Lakehouse architectures
- Integrate AI solutions with enterprise data pipelines and systems.
Exigences
Role Summary
- Design and build intelligent agent-based systems that can reason, plan, and act autonomously.
- Strong Python engineering expertise and hands-on experience with modern agent frameworks.
- Solid understanding of data platforms and scalable architectures.
Agent & AI System Development
- Design and build agent-based systems using frameworks such as LangChain, LangGraph, or similar.
- Develop intelligent components capable of reasoning, planning, and executing tasks autonomously.
- Implement advanced cognitive patterns such as ReAct (Reasoning + Acting).
LLM Capabilities & Enhancements
- Develop and integrate memory, tool usage, and context management capabilities (MCP).
- Build systems that leverage tool calling, chaining, and orchestration of LLM workflows.
- Collaborate with prompt engineers to enhance model responses and performance.
Engineering & Development
- Write high-quality, scalable code using Python, including async programming.
- Build and maintain APIs and microservices for AI/agent-based applications.
- Ensure systems are efficient, reliable, and production-ready.
Guardrails & Responsible AI
- Design and implement guardrails and safety mechanisms for LLM-driven systems.
- Ensure robust handling of edge cases, failure scenarios, and unintended outputs.
Data & Platform Integration, Work with modern data platforms such as:
- Snowflake
- Databricks
- Lakehouse architectures
- Integrate AI solutions with enterprise data pipelines and systems.
