Campus Undergraduate Summer Internship Program - 2027 AI Engineer, Enterprise Technology Services- Toronto, Ontario, CN

About the Team

Required Qualifications

• Currently enrolled in a full-time Bachelor’s degree program in Computer Science, Artificial Intelligence, Machine Learning, Cybersecurity, Computer Engineering, Software Engineering, Information Systems, or another related technical field.
• Students must have a graduation date between December 2027 and June 2028.
• Hands-on programming experience, preferably with Python, and exposure to one or more languages such as Java, JavaScript/Node.js, Go, C/C++, Bash, PowerShell, or similar technologies.
• Foundational understanding of computer science and software engineering concepts, including data structures, algorithms, APIs, debugging, testing, version control, and problem solving.
• Foundational understanding of artificial intelligence, machine learning, generative AI, LLMs, AI agents, or related concepts through coursework, research, projects, labs, or extracurricular activities.
• Basic understanding of cybersecurity principles, threats, vulnerabilities, security controls, application security, cloud security, threat modeling, or secure software development practices.
• Ability to learn new technologies, investigate technical problems, build or test working solutions, analyze results, and document findings with appropriate guidance.
• Strong analytical, problem-solving, written and verbal communication, collaboration, curiosity, and learning agility with the ability to work effectively in a research and engineering team environment.

Preferred Qualifications

• Demonstrated hands on experience through academic coursework, research, personal projects, open-source contributions, security labs, hackathons, Capture-the-Flag competitions, or other extracurricular technical work. Previous internship experience is not required.
• Interest in the intersection of artificial intelligence, cybersecurity, software engineering, and emerging technologies, including AI security, agent security, application security, cloud security, security automation, or secure AI enabled software development.
• Experience building software projects, prototypes, proof-of-concepts, research experiments, test harnesses, intelligent assistants, AI agents, agentic workflows, or hackathon solutions.
• Familiarity with LLMs, generative AI, prompt engineering, embeddings, retrieval-augmented generation, tool or function calling, orchestration frameworks, model evaluation, or human-in-the-loop review.
• Exposure to security research or testing techniques such as threat modeling, vulnerability research, AI red teaming, automated security testing, agent security testing, or evaluation of AI-native cybersecurity tools.
• Familiarity with APIs, cloud platforms, containers, data pipelines, development environments, security tools, or software integration patterns.
• Experience designing test cases, benchmarks, experiments, or technical evaluations and using evidence to summarize effectiveness, limitations, risks, and recommendations.
• Awareness of secure software development, responsible AI, data protection, privacy, governance, compliance, and responsible handling of sensitive information.
• Strong initiative, responsible judgment, attention to detail, presentation skills, and comfort working collaboratively in an experimental, fast learning environment.

Responsibilities

• What type of work can you expect? How will you make an impact in this role?
• Research emerging artificial intelligence and cybersecurity technologies, threats, techniques, and security capabilities with guidance from experienced engineers and researchers.
• Build prototypes, proof-of-concepts, security test harnesses, and experimental environments using Python and other modern programming languages.
• Assist in developing and testing AI and agentic AI solutions, including LLM integrations, AI agents, tool calling, orchestration frameworks, retrieval patterns, and automated workflows.
• Experiment with AI models for cybersecurity and software engineering use cases such as security analysis, threat detection, vulnerability research, application security testing, and automation.
• Integrate APIs, AI models, security tools, cloud services, containers, data sources, and development environments to support research and prototyping.
• Develop test cases, benchmarks, and experiments to evaluate solution effectiveness, reliability, security, limitations, and potential enterprise applications.
• Support hands-on evaluations of open-source technologies, products, platforms, and emerging technical capabilities, helping validate technical claims through testing and analysis.
• Analyze experimental results and document findings, assumptions, risks, technical limitations, and recommendations while following responsible AI, security, privacy, governance, and compliance expectations.
• Prepare technical documentation, research summaries, demonstrations, and presentations; share findings with AI, cybersecurity, engineering, architecture, product, and business stakeholders; and participate in Agile team practices and code reviews.