Python AI Engineer

Apptad Inc; Montreal; Hybrid; CAD 120,000 - 180,000; Full time

Job summary

Apptad Inc in Montreal, QC is seeking a Senior Python AI Engineer to design, develop, and deploy enterprise-grade AI agents and multi-agent systems with hands-on experience in modern agentic frameworks. The role requires collaboration with product and engineering teams to translate business needs into AI-driven solutions and to optimize LLM performance, reliability and safety.

The position is long-term and involves approximately three on-site days per week in Montreal, offering a hybrid work

Qualifications

• Strong Python development experience.
• Hands-on experience with Amazon Bedrock and AgentCore.
• Expertise in LangChain and LangGraph.
• Experience with Strands Agents SDK or similar agent frameworks.
• Deep understanding of AI Agent Design Patterns.
• Experience implementing Multi-Agent Systems.
• Knowledge of MCP (Model Context Protocol).
• Strong understanding of prompt engineering and LLM orchestration.

Responsibilities

• Design and develop autonomous AI agents and multi-agent workflows.
• Build agentic applications using Amazon Bedrock, AgentCore, LangChain, LangGraph, and Strands Agents SDK.
• Implement orchestration, planning, memory management, and tool-calling capabilities.
• Design and integrate Model Context Protocol (MCP) based solutions.
• Create scalable agent architectures following industry best practices and agent design patterns.
• Collaborate with product and engineering teams to translate business requirements into AI-driven solutions.
• Evaluate and optimize LLM performance, reliability, and safety.

Skills

Python

Amazon Bedrock

AgentCore

LangChain

LangGraph

Strands Agents SDK

AI Agent Design Patterns

Multi-Agent Systems

Model Context Protocol

Prompt engineering

LLM orchestration

Job description

Job Title: Python AI Engineer

Job Location

Montreal, QC (3days onsite in a week)
Job Duration: Long Term

Role Summary

We are seeking a Senior AI Agent Engineer (around 6 to 8 years of experience) to design, develop, and deploy enterprise-grade AI agents and multi-agent systems using modern agentic AI frameworks. The ideal candidate should have hands-on experience with Amazon Bedrock, AgentCore, LangChain, LangGraph, MCP, and AI agent design patterns.

Key Responsibilities

• Design and develop autonomous AI agents and multi-agent workflows.
• Build agentic applications using Amazon Bedrock, AgentCore, LangChain, LangGraph, and Strands Agents SDK.
• Implement orchestration, planning, memory management, and tool-calling capabilities.
• Design and integrate Model Context Protocol (MCP) based solutions.
• Create scalable agent architectures following industry best practices and agent design patterns.
• Collaborate with product and engineering teams to translate business requirements into AI-driven solutions.
• Evaluate and optimize LLM performance, reliability, and safety.

Required Skills

• Strong Python development experience.
• Hands-on experience with Amazon Bedrock and AgentCore.
• Expertise in LangChain and LangGraph.
• Experience with Strands Agents SDK or similar agent frameworks.
• Deep understanding of AI Agent Design Patterns.
• Experience implementing Multi-Agent Systems.
• Knowledge of MCP (Model Context Protocol).
• Strong understanding of prompt engineering and LLM orchestration.

Preferred Qualifications

• Experience with cloud-native deployments on AWS.
• Exposure to RAG-based architectures.
• Familiarity with observability, evaluation, and monitoring of AI agents.
• Knowledge of productionizing GenAI applications.