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Added 7 mins ago
Data Scientist
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Added 20 mins ago
System Engineer
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Technical skills such as coding (Python/R), data modeling, and database management (SQL)
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Technical skills such as coding (Python/R), data modeling, and database management (SQL)
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Added 37 mins ago
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Added 37 mins ago
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…credit models and support analytic reviews leveraging SQL, Python, Pyspark or data visualization…
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Added 37 mins ago
Business Systems Developer
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Charger Logistics Inc.

Senior AI Engineer

Brampton, ON, Canada

Job type: Full-time
Apply by: Oct 25, 2026
Posting language: English
Posted: Sep 25, 2026

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Original job description

Charger logistics Inc. is a world- class asset-based carrier with locations across North America. With over 20 years of experience providing the best logistics solutions, Charger logistics has transformed into a world-class transport provider and continue to grow.

We are looking for a highly motivated AI Engineer to join our team based out of our Brampton office and contribute to the development of AI-driven solutions for various departments. This role focuses on building production AI agents and MCP (Model Context Protocol) integrations that automate real logistics workflows - dispatch, billing, compliance, and fleet operations - improving the reliability, transparency, and efficiency of AI applications in real-world, high-stakes environments.

Responsibilities:

Design, develop, and deploy MCP servers exposing domain services as AI-consumable tools with proper authentication, observability, and error handling.
Build multi-agent workflows using orchestration frameworks and agent-to-agent communication protocols for complex logistics automation.
Develop and optimize knowledge retrieval pipelines using RAG, KAG, and CAG strategies - selecting the right approach based on query complexity, data volatility, and domain reasoning requirements.
Design hybrid retrieval architectures that route between CAG for static reference data, RAG for dynamic operational queries, and KAG for multi-hop reasoning across structured domain knowledge.
Implement LLM integration layers - prompt engineering, function calling, structured output parsing, and model routing for domain accuracy.
Collaborate with cross-functional teams to collect requirements and translate operational workflows into agent capabilities.
Deploy and maintain agent infrastructure on Kubernetes with GitOps practices and observability tooling.

Requirements

2-3 years of experience with Bachelor's in Computer Science, Artificial Intelligence, or a related technical field.
Strong communication skills and experience working in interdisciplinary or team-based environments.
Solid understanding of REST APIs, microservices architecture, and AI/ML concepts.
Experience building production-grade AI applications in Python - not just notebooks or prototypes.
Hands-on proficiency with LLM integration: function calling, tool use, structured outputs (OpenAI, Anthropic, or Google APIs).
Solid understanding of knowledge retrieval patterns including RAG (Retrieval-Augmented Generation), with familiarity of emerging approaches like KAG (Knowledge-Augmented Generation) and CAG (Cache-Augmented Generation).
Proficiency with SQL and at least one analytical data platform (BigQuery, Snowflake, or similar).
Experience with cloud platforms and container orchestration (Kubernetes).
Background in MCP, agent orchestration frameworks, knowledge graphs, or streaming data systems is a strong asset.

Benefits

Competitive Salary
Healthcare Benefit Package
Career Growth

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More about this job

Responsibilities

Design, build, and deploy production AI agents, MCP servers, and multi-agent workflows to automate logistics operations such as dispatch, billing, compliance, and fleet management. Develop retrieval and LLM integration systems, and maintain agent infrastructure on Kubernetes using GitOps and observability practices.

Requirements

Requires 2–3 years of experience and a bachelor's degree in Computer Science, Artificial Intelligence, or a related technical field, along with strong communication and teamwork skills. Candidates should have production Python AI application experience, LLM integration expertise, knowledge of retrieval approaches, SQL and analytical data platform proficiency, and experience with cloud platforms and Kubernetes.

Skills

Python
Artificial Intelligence
Function Calling
Agent Orchestration
Model Context Protocol
Retrieval-Augmented Generation
Knowledge-Augmented Generation
Cache-Augmented Generation
REST APIs
Microservices
SQL
Kubernetes
Cloud Platforms
Knowledge Graphs
Observability

Benefits

Healthcare Benefit Package
Career Growth

Visa sponsorship

Not detected in the job text

Keywords

Python
Artificial Intelligence
AI Agents
Model Context Protocol
MCP Servers
Multi-Agent Workflows
Agent Orchestration
Agent-to-Agent Communication
Retrieval-Augmented Generation
Knowledge-Augmented Generation
Cache-Augmented Generation
Hybrid Retrieval
Large Language Models
Prompt Engineering
Function Calling
Structured Outputs
Model Routing
REST APIs
Microservices
SQL
BigQuery
Snowflake
Kubernetes
GitOps
Observability
Knowledge Graphs
Streaming Data Systems
Logistics Automation
Dispatch
Fleet Operations

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