Senior AI Engineer

Urban Ridge Supplies; Brampton; On-site; CAD 90,000 - 130,000; Full time

Benefits offered by this job

Competitive Salary

Healthcare Benefit Package

Career Growth

Job summary

Charger logistics Inc. in Brampton is seeking a highly motivated AI Engineer to build production AI agents and MCP integrations that automate real logistics workflows across dispatch, billing, compliance, and fleet operations.

You will deploy on Kubernetes with GitOps, design multi-agent workflows, and optimize retrieval pipelines using RAG, KAG, and CAG, collaborating with cross-functional teams to translate operations into robust AI solutions.

Qualifications

• 2-3 years of experience with Bachelor's in Computer Science, Artificial Intelligence, or a related technical field.
• Strong communication skills and ability to work in interdisciplinary teams.
• Solid understanding of REST APIs, microservices, and AI/ML concepts.
• Experience building production-grade AI applications in Python.
• Hands-on experience with LLM integration: function calling, tools, structured outputs.
• Familiarity with Retrieval-Augmented Generation (RAG) and Knowledge-Augmented/Cache-Augmented Generation (KAG/CAG).
• Proficiency with SQL and analytical data platforms (BigQuery, Snowflake).
• Experience with cloud platforms and Kubernetes.

Responsibilities

• Design, develop, and deploy MCP servers exposing domain services as AI tools with authentication and observability.
• Build multi-agent workflows using orchestration frameworks and agent-to-agent communication protocols.
• Develop and optimize retrieval pipelines using RAG, KAG, and CAG strategies for dynamic data.
• Design hybrid retrieval architectures routing between CAG, RAG, and KAG for complex queries.
• Implement LLM integration layers including prompting, function calling, and structured outputs.
• Collaborate with cross-functional teams to translate workflows into agent capabilities.
• Deploy and maintain agent infra on Kubernetes with GitOps and observability tooling.

Skills

AI/ML concepts

REST APIs

microservices

Python production-grade

LLM integration

RAG/KAG/CAG

SQL

data platforms

Kubernetes

GitOps

MCP

Education

Bachelor's in Computer Science/AI or related

Tools

BigQuery

Snowflake

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