AI/LLM Engineer
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Key skills for this role
About the Role
Apptoza Inc. is seeking an experienced AI/LLM Engineer to design and build agent-based systems using LangChain and LangGraph. The role involves developing LLM capabilities, building APIs and microservices, and implementing guardrails for responsible AI.
Key Skills for This Role
Responsibilities
- Design and build agent based systems using LangChain and LangGraph
- Develop and integrate memory, tool usage, and context management capabilities
- Build and maintain APIs and microservices for AI/agent based applications
- Implement guardrails and safety mechanisms for LLM driven systems
- Integrate AI solutions with enterprise data pipelines and systems
Requirements
- 8+ years of experience
- Experience with LangChain and LangGraph
- Proficiency in Python including async programming
- Experience building APIs and microservices
- Experience with Snowflake and Databricks
Full Job Posting
Role Overview
- Role name: AI/LLM Engineer
- Location: Montreal 3days (hybrid)
- Duration: Contract / Full Time
- Exp Level: 8+ years
Key Responsibilities
- 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
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