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

At American Express, we empower future technologists to learn, experiment, and make an impact from day one. As an AI Engineer Intern focused on AI Security Research in Enterprise Technology Services, you’ll join a 16-week Summer Internship Program and contribute to hands-on projects at the intersection of artificial intelligence, cybersecurity, and software engineering. You’ll research emerging technologies, build working prototypes and proof-of-concepts, evaluate technical approaches, and learn how solutions are designed, tested, documented, and delivered in a global enterprise environment. In this role, you may explore AI security, agentic AI, application security, generative AI and advanced AI models for cybersecurity, security automation, cloud security, secure software development, and other emerging technologies. You’ll work with AI engineers, cybersecurity engineers, researchers, architects, product partners, and business stakeholders to turn research ideas into code, experiments, measurable results, and reusable capabilities while applying responsible AI, security, privacy, and governance practices. About the Team Enterprise Technology Services teams build and operate technology that helps American Express deliver trusted, secure, and customer-first products and services. The AI Security Research team explores emerging AI and cybersecurity capabilities, develops prototypes and experimental environments, and evaluates how new technologies may be applied responsibly and securely in an enterprise setting. As an undergraduate AI Engineer Intern, you’ll contribute at an early-career level with guidance from experienced engineers and researchers. You’ll gain practical experience investigating technical problems, building and testing solutions, analyzing results, and communicating findings to technical and non-technical partners. 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. 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.