Campus Undergraduate Summer Internship Program - 2027 AI Engineer, Enterprise Technology Services- New York, NY

American Express•Phoenix, NY

4d•Onsite

About The Position

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, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company. At American Express, we empower future technologists to learn, innovate, and make an impact from day one. As an AI Engineer Intern in Enterprise Technology Services, 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. You’ll build software, collaborate with Agile teams, and learn how products are designed, developed, tested, and delivered in a global enterprise environment. In this role, you may support work across machine learning, generative AI, intelligent automation, data pipelines, retrieval patterns, model evaluation, AI agents, agentic workflows, or AI-enabled software features. You’ll work with engineers, product partners, data practitioners, security partners, and business stakeholders to learn how enterprise AI solutions are designed and delivered responsibly, reliably, and securely.

Requirements

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.

Nice To Haves

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.

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.