Campus - Full Time - Software Engineer - 2027 (UK - London)

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 back 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, and in an environment where everyone is seen, heard and feels like they belong.

Join Team Amex and let’s lead the way together.

Role Summary

At American Express, we empower technologists to learn, innovate, and make an impact from day one. As a Software Engineer in the full-time Technology Graduate Program, you’ll join a 12-month technical and leadership development experience while contributing as a full-time colleague on an Enterprise Technology Services team. You’ll build software, collaborate with Agile teams, and help deliver secure, reliable, customer-first technology that supports the future of payments.

About the Team

Enterprise Technology Services teams build, operate, and modernize the technology that helps American Express deliver trusted, secure, and customer-first products and services. Software Engineers may support teams across backend engineering, frontend engineering, cloud engineering, mobile, AI/ machine learning, data-oriented engineering, infrastructure-adjacent engineering, or full-stack product development. You will design, code, test, improve, and support applications and services that help customers, colleagues, and partners get work done reliably and securely.

What Type Of Work Can You Expect?

• Develop, test, and improve software applications as part of an Agile scrum team.
• Write clean, maintainable code; participate in code reviews; and create unit tests with guidance from experienced engineers.
• Identify opportunities to apply new technologies, automation, and engineering practices to solve real business challenges.
• Partner with Product Managers, Senior Engineers, Quality Engineers, Architects, and business partners to understand requirements, prioritize features, and deliver value.
• Work across different parts of the technology stack, such as APIs, services, microservices, user interfaces, mobile experiences, cloud platforms, or data-driven solutions.
• Explore responsible use of AI-powered developer tools, machine learning concepts, and intelligent automation relevant to your team’s work.
• Participate in graduate program learning, mentorship, networking, community, and career-development experiences while building your full-time career at American Express.

What You’ll Learn

• How software is built and delivered “the Amex Way,” including structured onboarding, developer bootcamp concepts, code quality, testing, and secure engineering practices.
• How Product, Engineering, Quality, Security, and business partners collaborate from idea to production.
• How to translate customer or business needs into technical solutions while balancing quality, resilience, usability, and risk.
• How to communicate progress, ask effective questions, and share technical work with both technical and non-technical partners.
• How to grow through mentorship, feedback, technical learning, leadership exposure, and a strong graduate cohort community.
• Must have earned a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Software Engineering, or another technical field before the full-time start date.
• Students must have a graduation date between December 2026 and June 2027

Minimum Qualifications

• Experience developing products or projects in an academic, personal, internship, research, open-source, hackathon, or professional setting.
• Exposure to backend engineering, frontend engineering, cloud engineering, mobile engineering, AI / machine learning, data engineering, API development, or full-stack product development.
• Familiarity with Java, JavaScript, React, TypeScript, Python, C#, Go, Kotlin, Node.js, REST APIs, SQL, Spring, or similar frameworks and tools.
• Exposure to cloud-native development, microservices, containerization, CI/CD, DevOps, automated testing, accessibility, or secure software development concepts.
• Interest in AI-powered development tools, generative AI, intelligent automation, responsible AI, or machine learning fundamentals.

Preferred Qualifications

• Programming experience through coursework, projects, research, internships, open-source contributions, hackathons, or extracurricular activities using one or more languages such as Java, JavaScript, Python, C#, Go, Kotlin, Node.js, or similar technologies.
• Interest in building software applications across web, mobile, backend, cloud, API, microservices, or full-stack environments.
• Exposure to software development across backend, frontend, cloud, mobile, API, data, or full-stack environments.
• Exposure to advanced AI software engineering concepts such as LLM integrations, prompt engineering, prompt evaluation, embeddings, retrieval-augmented generation, vector search, AI agents, agentic workflows, or human-in-the-loop review.
• Familiarity with building or integrating AI-enabled applications using APIs, data pipelines, model inference endpoints, evaluation workflows, or cloud-based AI services.
• Awareness of responsible AI practices, including model reliability, explainability, privacy, security, governance, bias mitigation, guardrails, and validation of AI-generated outputs.
• Experience with modern software development practices such as version control, testing, code reviews, Agile methodologies, and collaborative development.
• Curiosity for emerging technologies, including artificial intelligence, machine learning, developer productivity tooling, automation, and responsible AI practices.
• Strong communication, teamwork, collaboration, learning agility, and the ability to learn emerging technologies