Manager AI Engineering-CA

Job summary

Design, build, integrate, and operationalize secure, governed, and scalable AI applications, agents, workflows, and reusable services that address business needs. Integrate solutions with enterprise data and platforms, and support deployment, monitoring, evaluation, risk controls, documentation, and continuous improvement.

Job details

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 AI Engineering 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, red-teaming, hallucination mitigation, safety controls, and continuous improvement practices for AI systems* Candidates with an equivalent combination of education, training, and experience will be considered 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 experienceGoogle Cloud, Vertex AI, Machine Learning Engineer, Data Engineer, or related cloud or AI certification*Candidates with equivalent practical experience, education, or training will be considered*Any requirement above marked with (*) would be considered as an asset (not mandatory) Competencies We Care About Each Other We Strive for Excellence We Succeed Together We Lead Responsibly Vision and strategic thinking Impactful and inclusive leadership Performance and value delivery Empowerment and talent development Strategic communication and influence Managerial courage and decisiveness Compliance Customer service AI Literacy and data orientation High-Impact Execution Process optimization Technical Skills/Knowledge Strong programming skills in Python and Structured Query Language (SQL), with experience using APIs, Git, CI/CD, testing, and software engineering practices Knowledge of AI frameworks and tools such as LangChain, LangGraph, CrewAI, AutoGen, FastAPI, Streamlit, Docker, Kubernetes, or related technologies Understanding of data governance, data quality, metadata, lineage, security, privacy, Responsible AI, and enterprise technology delivery practices

What you’ll do

Design, build, integrate, and operationalize secure, governed, and scalable AI applications, agents, workflows, and reusable services that address business needs. Integrate solutions with enterprise data and platforms, and support deployment, monitoring, evaluation, risk controls, documentation, and continuous improvement.

Requirements

Requires 2–5 years of experience in software, data, machine learning, or AI engineering, including experience delivering enterprise AI applications and working with generative AI, LLMs, RAG, and related techniques. Requires a bachelor's degree or equivalent experience, strong Python and SQL skills, and familiarity with AI frameworks, cloud and data platforms, software engineering practices, and responsible AI controls.

Listed skills

• Machine learning · Preferred
• prompt engineering · Preferred
• Python · Preferred
• SQL · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• AI Engineering
• Generative AI
• Machine Learning
• Large Language Models
• Retrieval-Augmented Generation
• Prompt Engineering
• AI Agents
• Python
• SQL
• Google Cloud Platform
• Vertex AI
• Gemini Enterprise
• Databricks
• Data Engineering
• AI Governance
• Model Evaluation

Job areas

• Technology
• Software
• Data & Analytics
• Management & Leadership
• Transportation

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