Software Engineer

Minimum Qualifications:

• 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
• 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, explain ability, 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.

Employment eligibility to work with American Express in the United Kingdom is required as the company will not pursue visa sponsorship for these positions.
 

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.

Minimum Qualifications:

• 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
• 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, explain ability, 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.

Employment eligibility to work with American Express in the United Kingdom is required as the company will not pursue visa sponsorship for these positions.