Manager AI Engineering-CA

Role overview

AI engineering and delivery

• Design, develop, test, and deploy AI-powered applications, agents, and intelligent workflows.
• Build generative AI, machine learning, and automation solutions using approved engineering patterns, platforms, and controls.
• Implement RAG, prompt engineering, model evaluation, and workflow automation patterns.
• Develop reusable APIs, services, and components to accelerate consistent AI delivery.

Data, platforms, and operations

• Integrate AI solutions with enterprise applications, data platforms, business processes, and operational workflows.
• Develop and optimize secure, scalable data pipelines, services, and interfaces.
• Contribute to enterprise platforms including Databricks, Gemini Enterprise, and Vertex AI.
• Apply governance, security, privacy, Responsible AI, and model risk controls across the lifecycle.
• Support deployment, monitoring, troubleshooting, evaluation, red-teaming, hallucination mitigation, and continuous improvement.
• Document technical designs, decisions, limitations, and operational requirements.

Experience and education

• Requires 2–5 years in software engineering, data engineering, machine learning engineering, AI engineering, or related technology delivery.
• Experience building enterprise copilots, chatbots, document intelligence solutions, workflow assistants, AI agents, or agentic applications.
• Experience with generative AI, LLMs, RAG, vector search, embeddings, prompt engineering, agents, and model evaluation.
• A related bachelor’s degree or equivalent experience; equivalent practical experience, education, or training is considered.
• Cloud AI and data platform experience and specified observability and safety practices are assets, not mandatory.

Technical skills

• Strong Python and SQL programming, with APIs, Git, CI/CD, testing, and software engineering practices.
• Knowledge of frameworks and tools such as LangChain, LangGraph, CrewAI, AutoGen, FastAPI, Streamlit, Docker, or Kubernetes.
• Understanding of data governance, data quality, metadata, lineage, security, privacy, and Responsible AI.

Working conditions

• Standard office working conditions, Monday to Friday, with eligibility for CN’s hybrid work model.
• The role involves managing priorities and delivering work within established timelines.

Compensation

• The hiring salary range is $110,000–$144,000; salary is determined individually based on skills and experience.
• The role is also eligible for an annual bonus, employee share investment program, pension, benefits, and other perks.