Solution Architect

Canadian National Railway Company • Montreal, QC

5d

About The Position

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
We are seeking a highly skilled AI Architect to lead the hands-on design, development, and implementation of our data and AI platforms on Google Cloud Platform (GCP) and Databricks. This is a practical, hands-on role requiring you to not only architect solutions but also to actively build, test, and deploy them. The ideal candidate will be a thinker with deep, demonstrable technical expertise in building and scaling end-to-end AI solutions, including Conversational AI and Agentic AI systems. You will play a critical, hands-on role in executing our data strategy, driving innovation, and enabling data-driven decision-making across the organization.

Requirements

• Deep, demonstrable technical expertise in building and scaling end-to-end AI solutions, including Conversational AI and Agentic AI systems.
• Hands-on expertise in designing, developing, and implementing data and AI platforms on Google Cloud Platform (GCP) and Databricks.
• Proficiency in architecting and designing AI solutions using Databricks and/or GCP Vertex AI, Gemini, etc.
• Experience in designing and prototyping advanced AI systems, including conversational AI (chatbots, voice assistants) and autonomous agentic AI frameworks.
• Experience integrating traditional ML and Generative AI models using MLflow and other MLOps best practices.
• Experience building, testing, and deploying conversational AI and agentic AI solutions, leveraging large language models (LLMs) and frameworks like Google's Vertex AI and open-source alternatives within the Databricks Platform.
• Experience building and deploying real-time streaming solutions using Structured Streaming.
• Experience optimizing data and AI pipelines for performance, cost, and scalability.
• Hands-on expertise on both GCP and Databricks, including practical guidance on best practices, security, and governance.
• Hands-on experience with services like Databricks, Google Cloud Storage, BigQuery, and Vertex AI (including the Gemini family of models).
• Experience implementing robust access controls, encryption, and other security measures.
• Experience monitoring, troubleshooting, and optimizing platforms for cost and performance.

Responsibilities

• Contribute to the hands-on design of our end-to-end Databricks Lakehouse platform, from data ingestion and processing to consumption and governance.
• Architect and design AI solutions built on Databricks and/or GCP Vertex AI, Gemini, etc.
• Design and prototype advanced AI systems, including conversational AI (chatbots, voice assistants) and autonomous agentic AI frameworks.
• Actively integrate traditional ML and cutting-edge Generative AI models into our data ecosystem using MLflow and other MLOps best practices.
• Build, test, and deploy conversational AI and agentic AI solutions, leveraging large language models (LLMs) and frameworks like Google's Vertex AI and open-source alternatives within the Databricks Platform.
• Personally build and deploy real-time streaming solutions using Structured Streaming to enable timely insights for AI models.
• Contribute to optimize initiatives of data and AI pipelines for performance, cost, and scalability, ensuring the efficient use of our cloud resources.
• Hands-on expert on both GCP and Databricks, providing practical guidance on best practices, security, and governance.
• Design and implement solutions that leverage the best of both platforms, including hands-on work with services like Databricks, Google Cloud Storage, BigQuery, and Vertex AI (including the Gemini family of models).
• Take direct responsibility for implementing robust access controls, encryption, and other security measures to ensure the security and compliance of our data platform.
• Continuously monitor, troubleshoot, and optimize our platform for cost and performance.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed