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Highest Level Division: Technology Operations & Enablement

Posting Start Date: 11/2/26

Posting End Date: 09/26/26 11:59 EDT

Hiring Salary Range: $110000 - 144000

This range represents the hiring range. Salaries are determined individually depending on skills and experience. You will also be eligible to an annual bonus, employee share investment program (ESIP), Pension, Perks and other perks.

At CN, we are committed to our pursuit of excellence. We take pride in delivering work of the highest standard, continually innovating to shape the railroad of the future. As responsible railroaders, we make the right decisions every time, putting safety first, acting with unwavering integrity, and holding ourselves accountable for our actions. We believe in succeeding together—by fostering inclusivity and collaboration, we sustainably deliver exceptional results for our customers.

Job Summary

The incumbent is responsible for designing, building, integrating, and operationalizing enterprise artificial intelligence (AI) solutions that support CN's next generation of data, analytics, automation, and agentic capabilities. The role translates business opportunities into production-grade AI applications, AI agents, intelligent workflows, reusable components, and platform-integrated services. The incumbent works across software engineering, data engineering, machine learning, and generative AI to deliver secure, governed, reliable, and scalable AI solutions using CN-approved platforms and patterns. The role collaborates with AI architects, platform engineers, AI operations, data scientists, data engineers,



business partners, cybersecurity, governance, architecture, and vendor teams to move AI use cases from concept to production.

Main Responsibilities

AI Engineering and Solution Delivery

- Design, develop, test, and deploy AI-powered applications, AI agents, and intelligent workflows that address business needs and deliver measurable value
- Build and enhance generative AI, machine learning, and automation solutions using CN-approved engineering patterns, platforms, and controls
- Implement Retrieval Augmented Generation (RAG), prompt engineering, model evaluation, and AI workflow automation patterns to support scalable production solutions
- Develop reusable application programming interfaces (APIs), services, and components that accelerate AI delivery and promote consistency across use cases

Data and Platform Integration
- Integrate AI solutions with enterprise applications, data platforms, business processes, and operational workflows
- Develop and optimize data pipelines, services, and interfaces that support reliable, secure, and scalable AI applications
- Contribute to enterprise AI platforms, including Databricks, Gemini Enterprise, Vertex AI, and related technologies, to support solution delivery
- Collaborate with data engineers, platform teams,



and business partners to ensure AI solutions are aligned with enterprise architecture, data quality, and operational requirements

Governance, Operations and Continuous Improvement
- Apply AI governance, security, privacy, Responsible AI, and model risk controls throughout the solution lifecycle
- Support production deployment, monitoring, troubleshooting, quality evaluation, red-teaming, hallucination mitigation, and continuous improvement of AI solutions
- Document technical designs, decisions, limitations, and operational requirements to support maintainability, auditability, and successful handover

Working Conditions

The role has standard working conditions in an office environment with a regular workweek from Monday to Friday and is eligible to participate in CN's hybrid work model. The role involves managing priorities and delivering work within established timelines, with support from the team to ensure sustainable and effective workload management. Requirements

Experience

- Between 2 to 5 years of experience in software engineering, data engineering, machine learning engineering, AI engineering, or related technology delivery roles
- Experience building enterprise copilots, chatbots, document intelligence solutions, workflow assistants, AI agents, or agentic applications
- Experience with generative AI, large language models (LLMs), Retrieval Augmented Generation (RAG), vector search, embeddings, prompt engineering, agents, and model evaluation
- Experience with Google Cloud Platform, Vertex AI, Gemini Enterprise, Databricks, Spark/PySpark, Delta Lake, Unity Catalog, MLflow, or comparable cloud AI and data platforms*
- Experience implementing observability; quality evaluation;

📌 Expert AI Engineering-CA (Montreal)
🏢 Canadian National
📍 Montreal