Campus Undergraduate Summer Internship Program - 2027 Cybersecurity AI Engineer, Enterprise Technology Services- Phoenix, AZ

The Enterprise Technology Services organization partners with every part of the American Express business to power the company's growth and innovation with trust and efficiency. As a Cybersecurity AI Engineer Intern, you'll join a 10-week Summer Internship Program and contribute to real-world technology projects that help teams explore, build, test, and responsibly scale AI-enabled solutions. ## Responsibilities - Support the development and integration of AI/ML models, LLM integrations, or intelligent services into controlled or production-like systems under guidance. - Assist with data collection, preprocessing, transformation, and management to enable model training, testing, validation, and evaluation. - Contribute to testing, debugging, and improving AI-enabled solutions to strengthen performance, reliability, explainability, and maintainability. - Support AI capabilities such as basic model training workflows, inference endpoints, prompt based interactions, evaluation routines, data retrieval pipelines, AI agents, or agentic workflows. - Collaborate with engineering, product, data, risk, security, and business partners to implement AI driven solutions aligned to business requirements. - Document model parameters, prompts, evaluation assumptions, data pipelines, system integrations, and technical decisions to support reproducibility. - Participate in Agile development practices, including sprint planning, stand ups, demos, retrospectives, code reviews, and team ceremonies. - Assist in ensuring AI systems and AI enabled features align with enterprise expectations for reliability, safety, governance, security, and compliance. - Build foundational confidence working across AI-adjacent technology areas such as APIs, cloud environments, data platforms, CI/CD, containers, model deployment patterns, and monitoring. ## Qualifications ## Minimum Qualifications - Currently enrolled in a full-time bachelor's degree program - Bachelor's degree candidates with an expected graduation date between December 2027 and June 2028. - Knowledge of Python and foundational data processing technologies. - Foundational understanding of computer science concepts, including data structures, algorithms, debugging, testing, and problem solving. - Understanding of machine learning concepts such as model training, evaluation, feature engineering, and experimentation. - Experience using modern AI systems such as LLM APIs, prompt-based interactions, retrieval patterns, or generative AI applications. - Awareness of responsible AI, security, governance, compliance, and reliability considerations. - Strong communication, collaboration, documentation, and learning agility with the ability to work effectively in a team environment. ## Preferred Qualifications - Demonstrated experience through academic coursework, research, projects, open-source contributions, internships, or extracurricular activities using Python, R, Java, JavaScript, or similar technologies. - Interest in machine learning, generative AI, natural language processing, intelligent automation, data engineering, agentic AI, or AI-enabled software development. - Experience building AI-powered applications, copilots, intelligent assistants, agentic workflows, research prototypes, or hackathon solutions using AI/ML technologies. - Familiarity with NLP techniques and model concepts such as fuzzy matching, embeddings, BERT, transformers, or other modern language models. - Exposure and experience with prompt engineering, prompt evaluation, tools, function calling, or agent workflow concepts. - Experience or coursework involving ML algorithms and applying them to practical or real-world problems. - Familiarity with APIs, data pipelines, ETL processes, cloud environments, or containerized development. - Awareness of CI/CD, version control, testing, code reviews, and collaborative software engineering workflows. - Curiosity for AI-powered developer tools, responsible AI practices, governance, security, and enterprise-scale delivery.