Amex Manifest
You Lead the Way. We’ve Got Your Back.
With the right backing, people and businesses have the power to progress in
incredible ways. When you join Team Amex, you become part of a global and
diverse community of colleagues with an unwavering commitment to backing our
customers, communities, and each other. Here, you’ll learn and grow as we help
you create a career journey that’s unique and meaningful to you, with benefits,
programs, and flexibility that support you personally and professionally.
At American Express, you’ll be recognized for your contributions, leadership,
and impact—every colleague has the opportunity to share in the company’s
success. Together, we’ll win as a team, striving to uphold our company values
and powerful backing promise to provide the world’s best customer experience
every day. And we’ll do it with the utmost integrity, in an environment where
everyone is seen, heard, and feels like they belong.
Join Team Amex and let’s lead the way together.
Business Unit / Role Specific Info
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.
About the Team
Enterprise Technology Services teams build and operate technology that helps
American Express deliver trusted, secure, and customer-first products and
services. Interns may be aligned to scrum teams across backend engineering,
frontend engineering, cloud engineering, mobile, AI / machine learning,
data-oriented engineering, or full-stack product development.
As an AI Engineer Intern, you’ll contribute at an early-career level while
learning how intelligent systems are built, validated, integrated, monitored,
and governed in an enterprise environment.
RESPONSIBILITIES
What type of work can you expect? How will you make an impact in this role?
• 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.
1. 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
Currently enrolled in a Master’s degree program in Computer Science, Machine
Learning, Data Science, Computer Engineering, or another technical field.
Minimum Qualifications
• 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.
AI Engineer Areas and Skills
AI Engineer Interns may support teams based on business needs, project
requirements, and individual strengths. Experience in one or more of the
following areas is beneficial:
• AI / Machine Learning Engineering: Python, R, Java, machine learning
fundamentals, model training, model evaluation, feature engineering, NLP,
embeddings, transformer models, LLM APIs, prompt engineering, retrieval
patterns, AI agents, model documentation, responsible AI concepts.
*
• Data Engineering for AI: Data collection, preprocessing, data quality, ETL,
data pipelines, SQL, big data concepts, data validation, feature pipelines,
and reproducible data workflows.
*
• AI-Enabled Software Engineering: APIs, microservices, inference endpoints,
application integration, cloud-native development, agile delivery, testing,
CI/CD, containerization, observability, and production-like deployment
practices.
*
• Generative AI / LLM Applications: Prompt-based interactions, LLM
integrations, retrieval-augmented generation concepts, evaluation of AI
outputs, grounding patterns, guardrails, AI agents, agent orchestration, and
human-in-the-loop review.
*
• Enterprise AI Readiness: Security, compliance, model governance,
documentation, risk awareness, system reliability, issue escalation, and
responsible AI practices.
*
• Cybersecurity & AI Security: Secure software development practices,
application security fundamentals, identity and access management, data
protection, encryption concepts, secure API design, vulnerability awareness,
threat modeling fundamentals, secure use of AI/LLM technologies, AI security
risks (prompt injection, data leakage, model abuse), governance controls,
compliance awareness, and responsible handling of sensitive information.
• What You’ll Learn
• How AI-enabled software is designed, built, tested, and delivered in an
enterprise technology environment.
• How machine learning, generative AI, LLM APIs, prompt-based workflows,
retrieval patterns, AI agents, agentic workflows, and model evaluation can be
applied to business problems.
• How Product, Engineering, Data, Security, Risk, and business partners
collaborate from idea to implementation.
• How to balance AI innovation with quality, resilience, usability, privacy,
security, compliance, and responsible AI expectations.
• How to communicate technical progress, ask effective questions, document your
work, and share outcomes with both technical and non-technical audiences.
• How to grow your career through mentorship, feedback, peer learning,
technical curriculum, and Early Careers programming.
• Foundational knowledge of computer science concepts such as data structures,
algorithms, object-oriented programming, debugging, testing, and
problem-solving.
• Foundational knowledge of machine learning concepts such as supervised
learning, unsupervised learning, feature engineering, model evaluation, and
basic experimentation.
At American Express, our culture is built on a 175-year history of
innovation, shared values
[https://www.americanexpress.com/en-us/company/who-we-are/]and Leadership
Behaviors, and an unwavering commitment to back our customers, communities, and
colleagues. From delivering differentiated products to providing world-class
customer service, we operate with a strong risk mindset, ensuring we continue to
uphold our brand promise of trust, security, and service.
As part of Team Amex, you’ll experience our powerful backing with comprehensive
support for your holistic well-being and many opportunities to learn new skills,
develop as a leader, and grow your career. Here, your voice and ideas matter,
your work makes an impact, and together, you will help us define the future of
American Express.
We back you with benefits that support your holistic well-being so you can be
and deliver your best. This means caring for you and your loved ones' physical,
financial, and mental health, as well as providing the flexibility you need to
thrive personally and professionally:
• Competitive base salaries
• Flexible work arrangements and schedules with hybrid and virtual options with
Amex Flex
• Free access to global on-site wellness centers staffed with nurses and
doctors (depending on location)
• Free and confidential counselling support through our Healthy Minds program
• Career development and training opportunities
Offer of employment with American Express is conditioned upon the successful
completion of a background verification check, subject to applicable laws and
regulations.