
Apptad
Actively Hiring
We help leading brands build Data and Analytics competencies
- B2B
- Growth StageExpanding market presence
Python AI Engineer (local candidates only)
- |6 years of exp
- |Contract
Posted: 4 days ago• Recruiter recently active
Job Location
Remote Work Policy
In office - WFH flexibility
Visa Sponsorship
Not Available
RelocationAllowed
Skills
Python
MCP
Prompt Engineering
LangChain
Amazon Bedrock
Langgraph
LLM Orchestration
AgentCore
Strands Agents SDK
About the job
Job Title: Python AI Engineer (local candidates only)
Job Location: Montreal, QC (3 days/week onsite)
Job Type: Contract- 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.
About the company
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