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Analyst, AI Engineer

At CN, everyday brings new and exciting challenges. You can expect an interesting environment where you're part of making sure our business is running optimally and safely-helping keep the economy on track. We provide the kind of paid training and opportunities that long-term careers are built on and we recognize hard workers who strive to make a difference. You will be able to thrive in our close-knit, safety-focused culture working together as ONE TEAM. The careers we offer are meaningful because the work we do matters. Join us! 

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 requires strong full-stack software engineering skills to translate business opportunities into production-grade AI applications, autonomous AI agents, intelligent workflows, and platform-integrated services. The incumbent works end-to-end-across frontend/backend development, data engineering, machine learning, and generative AI-to deliver secure, governed, reliable, and scalable AI solutions. A critical aspect of this role is taking ownership of the deployment lifecycle, utilizing CI/CD pipelines and DevOps/LLMOps best practices to move AI use cases from concept to production on CN-approved platforms.

Main Responsibilities

AI Engineering, Full-Stack Development, and Solution Delivery

       Design, develop, test, and deploy end-to-end full-stack AI-powered applications, autonomous 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.

       Architect and implement agentic workflows, Retrieval Augmented Generation (RAG), prompt engineering, and model evaluation patterns to support scalable production solutions.

       Develop reusable application programming interfaces (APIs), robust backend services, and interactive frontend components that accelerate AI delivery and promote consistency across use cases.
 Data Integration, CI/CD, and Deployment

       Lead the deployment of AI solutions into production environments, establishing and maintaining robust CI/CD pipelines for automated testing, integration, and delivery.

       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, applying LLMOps best practices to support solution delivery.

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. 

Requirements

Experience

AI & Full-Stack Engineering

       Over 2+ years of experience in full-stack development, AI engineering, data science, or related technology delivery roles with a strong focus on production deployments.

       Over 1 year of proven hands-on experience building and deploying enterprise copilots, chatbots, workflow assistants, autonomous AI agents, or agentic applications to production.

       Strong experience with CI/CD pipelines, DevOps/LLMOps practices, and deploying containerized applications into cloud environments.

       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, red-teaming, hallucination mitigation, safety controls, and continuous improvement practices for AI systems*

Any requirement above marked with (*) would be considered as an asset (not mandatory)

Education/Certification/Designation

       Bachelor's Degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Technology, Engineering, or a related field, or equivalent experience.

       Google Cloud, Vertex AI, Machine Learning Engineer, Data Engineer, or related cloud or AI certification*

Any requirement above marked with (*) would be considered as an asset (not mandatory)

Competencies

         Applies critical thinking
         Knows the business and stays current on industry needs
         Collaborates with others and shares information
         Communicates with impact
         Identifies needs and finds solutions to create value for all stakeholders
         Leads by example for the safety and security of all
         Identifies potential safety and security risks

Technical Skills/Knowledge

       Strong full-stack programming skills (Python, JavaScript/TypeScript, SQL), with extensive experience building and integrating RESTful APIs and modern frontends (e.g., React, Angular).

       Deep technical knowledge and hands-on experience with AI agent frameworks and tools such as ADK, LangChain, LangGraph, CrewAI, AutoGen, or LlamaIndex.

       Mandatory experience with modern deployment and DevOps tools: Git, CI/CD pipelines (e.g., GitHub Actions, GitLab CI, Jenkins), Docker, and Kubernetes.

       Experience with backend frameworks like FastAPI, Flask, or Node.js, and rapid prototyping tools like Streamlit.

       Understanding of data governance, data quality, metadata, lineage, security, privacy, Responsible AI, and enterprise technology delivery practices.
About CN 
CN is a world-class transportation leader and trade-enabler. Essential to the economy, to the customers, and to the communities it serves, CN safely transports more than 300 million tons of natural resources, manufactured products, and finished goods throughout North America every year. As the only railroad connecting Canada's Eastern and Western coasts with the Southern tip of the U.S. through a 19,500 mile rail network,CN and its affiliates have been contributing to community prosperity and sustainable trade since 1919. CN is committed to programs supporting social responsibility and environmental stewardship. At CN, we work as ONE TEAM, focused on safety, sustainability and our customers, providing operational and supply chain excellence to deliver results.