Expert System Architecture - Google Cloud Platform and Gemini Entreprise-CA

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, Benefits 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.

Join us today and get your career moving!

Job Summary

We are seeking a highly skilled incumbent with deep, hands-on experience designing, implementing, and optimizing enterprise-scale solutions on Google Cloud Platform (GCP), with proven delivery experience on Google Gemini Enterprise. This is a highly technical role requiring an individual who not only architects solutions but is also capable of personally building, deploying, troubleshooting, and optimizing cloud-native platforms, AI agents, and applications.

The incumbent serves as the organization's trusted Google Cloud and Gemini Enterprise expert, driving cloud and AI strategy and delivering scalable, secure, governed, and cost-effective solutions that accelerate business outcomes.

Main Responsibilities

Architecture and Design

Lead the hands-on design and implementation of end-to-end cloud solutions on Google Cloud Platform (GCP).

Architect secure, scalable, resilient, and highly available enterprise cloud environments.

Develop reference architectures, technical standards, cloud adoption roadmaps, and solution blueprints.

Design hybrid and cloud-native architectures supporting business-critical applications and services.

Define integration patterns across applications, platforms, data ecosystems, and third-party solutions.

Translate business requirements into scalable and sustainable technical solutions.

Engineering, Platform and AI Delivery

Personally build, configure, test, deploy, and support production-grade solutions across the GCP ecosystem.

Develop and maintain Infrastructure as Code (IaC) using Terraform and cloud automation best practices.

Build and deploy containerized solutions using Google Kubernetes Engine (GKE), Cloud Run, and other cloud-native services.

Design and implement CI/CD pipelines supporting automated deployment and operational excellence.

Lead cloud migration, modernization, and transformation initiatives from on-premises and multi-cloud environments.

Troubleshoot and resolve complex technical issues across cloud infrastructure, applications, integrations, and platforms.

Gemini Enterprise, Agentic AI and Cloud Expertise

Act as the hands-on technical lead and architect for the enterprise Gemini Enterprise platform, including reference architecture, landing zone, configuration, operating standards, and governance.

Configure and administer the Gemini Enterprise app, including identity federation, access controls, agent gallery, licensing, and usage analytics.

Design and implement data connectors, data stores, and secure access patterns across enterprise systems such as SharePoint, OneDrive, Google Drive, ServiceNow, Jira, Salesforce, BigQuery, Databricks, and Data Lakehouse platforms.

Build, deploy, and operate custom AI agents using Agent Development Kit (ADK), Agent Studio, Agent Runtime, Python, APIs, and Model Context Protocol (MCP).

Define the enterprise AI reference architecture, including patterns for retrieval-augmented generation (RAG), single and multi-agent systems, tool use, human-in-the-loop, model evaluation, and model fine-tuning.

Implement agent governance and security using Agent Gateway, Agent Identity, Agent Registry, IAM policies, Model Armor, VPC Service Controls, Sensitive Data Protection, and responsible AI guardrails.

Prepare and present AI and cloud solution architectures to enterprise architecture, cybersecurity, and governance review boards.

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 requires occasional business travel within Canada and the United States in accordance with CN policy.

Experience

Cloud, AI and Solution Architecture

10+ years of overall technology experience, including enterprise architecture, solution architecture, system architecture, cloud engineering, or related technology roles

Minimum 5 years of experience in Solution Architecture and/or Systems Architecture roles

Minimum 7 years of hands-on experience designing and implementing cloud solutions

Expert-level, end-to-end hands-on experience with Google Cloud Platform in large enterprise environments

Demonstrated hands-on experience architecting and delivering at least one enterprise Gemini Enterprise implementation in production, including connectors, identity integration, access controls, and governance

Minimum 3 years of experience in an AI, machine learning, or Generative AI architecture role, with solutions delivered to production

Experience with Databricks on Google Cloud Platform, transportation, logistics, supply chain, or industrial organizations*

Candidates with an equivalent combination of education, training, and experience will be considered

• Any requirement marked with (*) will be considered an asset (not mandatory)

Education/Certification/Designation

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field

Google Professional Cloud Architect Certification, Google Professional Cloud Security Engineer Certification, Google Professional Machine Learning Engineer Certification, Google Cloud Generative AI Leader Certification, Google Cloud Professional Agentic Architect Certification (Beta), TOGAF, ITIL, or SAFe Architect certification*

Candidates with equivalent practical experience, education, or training will be considered

• Any requirement marked with (*) will be considered an asset (not mandatory)

Competencies

We Care About Each Other

We Strive for Excellence

We Succeed Together

We Lead Responsibly

Compliance

Business acumen

High-Impact Execution

Conveying the vision

Coordination

Technical Skills/Knowledge

Expert knowledge of Google Cloud Platform services including Compute Engine, GKE, Cloud Run, Cloud Functions, Cloud Storage, BigQuery, Pub/Sub, Cloud SQL, AlloyDB, IAM, and Google Cloud Operations Suite

Hands-on experience with Gemini Enterprise, Gemini Enterprise Agent Platform, Agent Development Kit (ADK), Agent Studio, Agent Runtime, APIs, MCP, RAG, agent evaluation, and production AI agent operations

Deep understanding of LLM architecture patterns, including retrieval-augmented generation, agents and multi-agent orchestration, prompt engineering, embeddings, fine-tuning, vector databases, and responsible AI controls

Experience with cloud networking, identity and access management, encryption, key management, secrets management, security controls, compliance, and governance frameworks

Strong experience with Terraform, Infrastructure as Code, DevOps, CI/CD, Site Reliability Engineering, Kubernetes, containerization, and cloud-native application architectures

Experience designing modern data, analytics, streaming, batch, real-time, MLOps, LLMOps, AgentOps, and AI governance solutions using GCP-native technologies, Databricks, Kafka, and Data Lakehouse platforms

Knowledge of AI-specific risks including prompt injection, data leakage, hallucination, excessive agent autonomy, model drift, quality measurement, guardrails, and responsible AI practices

Excellent communication, stakeholder management, architecture review, technical leadership, mentoring, and strategic cloud planning skills

Additional Information (If Any)

About C