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Red Teaming information

What is red teaming?

Red Teaming is a cybersecurity practice where experts simulate real-world attacks on an organization's systems, networks, or processes to identify vulnerabilities and test defenses. Unlike traditional security testing, Red Teaming takes an adversarial approach, mimicking the tactics, techniques, and procedures of actual threat actors. The goal is to assess how well an organization can detect, respond to, and recover from sophisticated attacks, ultimately strengthening its overall security posture.

What are the key skills and qualifications needed to thrive as a red teamer?

To thrive as a Red Teamer, you need strong knowledge of cybersecurity principles, penetration testing, network protocols, and typically a degree in computer science or a related field. Familiarity with tools like Metasploit, Kali Linux, Burp Suite, and certifications such as OSCP or CEH are commonly required. Creative problem-solving, critical thinking, and effective communication are crucial soft skills that set exceptional Red Teamers apart. These competencies are essential to accurately simulate real-world cyber threats, identify vulnerabilities, and effectively communicate risks to improve organizational security.

How to get a job as a red teamer?

To become a red teamer, develop strong skills in cybersecurity, penetration testing, and scripting languages like Python or Bash. Obtain relevant certifications such as OSCP or CREST, gain experience with security tools like Kali Linux and Metasploit, and build a portfolio of simulated attack exercises to demonstrate your expertise.

Is red teaming in demand?

Red teaming is in high demand as organizations seek proactive cybersecurity measures to identify vulnerabilities. Professionals in this field with skills in penetration testing, threat simulation, and familiarity with tools like Kali Linux are increasingly sought after across various industries.

What are the typical challenges faced by professionals working in red teaming, and how can they overcome them?

Red Teaming professionals often encounter challenges such as staying updated with rapidly evolving security threats, gaining realistic access to target environments, and balancing creativity with ethical boundaries. Effective collaboration with Blue Teams and clear communication with stakeholders are essential for impactful assessments. To overcome these challenges, Red Teamers should engage in ongoing training, participate in security communities, and maintain a strong ethical framework while leveraging diverse technical skills and tools.

What are red teaming jobs?

Red teaming jobs involve simulating cyberattacks or security breaches to test an organization’s defenses. Professionals in these roles use skills in cybersecurity, penetration testing, and threat analysis to identify vulnerabilities and improve security measures, often working with tools like Kali Linux and adhering to ethical hacking standards.
What are popular job titles related to Red Teaming jobs in Quebec? For Red Teaming jobs in Quebec, the most frequently searched job titles are:
Red Teaming jobs near you
Infographic showing various Red Teaming job openings in Quebec as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Hybrid job distribution.

Expert, AI Engineer

Canadian National Railway Company

Montreal-est, QC

Full-time

Posted 11 days ago

Canadian National Railway rating

7.5

Company rating: 7.5 out of 10

Based on 49 frontline employees who took The Breakroom Quiz

136th of 359 rated logistics

Job description

Expert, 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 fordesigning, building, integrating, and operationalizing enterprise artificialintelligence (AI) solutions that support CN's next generation of data,analytics, automation, and agentic capabilities. The role translates businessopportunities into production-grade AI applications, AI agents, intelligentworkflows, reusable components, and platform-integrated services. The incumbentworks across software engineering, data engineering, machine learning, andgenerative AI to deliver secure, governed, reliable, and scalable AI solutionsusing CN-approved platforms and patterns. The role collaborates with AIarchitects, platform engineers, AI operations, data scientists, data engineers,business partners, cybersecurity, governance, architecture, and vendor teams tomove AI use cases from concept to production.
Main Responsibilities

AI Engineering andSolution 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 PlatformIntegration
  • 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 ContinuousImprovement

  •  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 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*

Any requirementabove 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
    TechnicalSkills/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

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)

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. 

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