At American Express, AI is reshaping the future of commerce and redefining the experiences our
commercial customers and card members expect. Within Amex Technology, we are building platforms,
products, and governance that enable agentic AI systems to operate responsibly and at scale across the
enterprise.
Our focus is on agentic AI development: designing intelligent, adaptive systems that can plan, reason,
and act across complex workflows with appropriate levels of autonomy. These systems power
autonomous workflows, decision support, and customer-facing experiences-while meeting the high
standards for security, explainability, reliability, and compliance required in financial services.
We partner closely with product, design, and business teams to deliver agentic capabilities that reduce
operational friction, improve decision-making, and transform how customers interact, transact, and grow.
As an AI Engineer - Agentic AI, you will be a hands-on builder contributing to the development of
production agentic AI systems that operate on real financial data and serve real customers.
You will work alongside experienced engineers, product managers, and designers to design, build, and
ship AI-powered features, while learning how to operate within a regulated, customer-facing environment.
This role offers strong mentorship and opportunities to grow your technical depth in LLMs, agentic
systems, and production AI engineering.
This is not a research-only role. You will write production code, contribute to system design discussions,
and help operate what you build after launch, with support and guidance from more senior engineers
At American Express, our culture is built on a 175-year history of innovation, shared values 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.
- 2+ years of professional software engineering experience.
- Some hands-on experience building or contributing to AI-powered features, LLM-based
applications, or applied ML systems (professional or project-based).
- Solid engineering fundamentals in at least one backend language (Python, Go, or TypeScript).
- Familiarity with APIs, basic cloud concepts, and modern development practices.
- Interest in agentic AI systems, autonomy, and AI-assisted development workflows.
- Willingness to learn, take feedback, and grow technical ownership over time.
- Comfort working in collaborative, cross-functional teams.
- A strong customer mindset and curiosity about real-world problem solving.
- Exposure to LLM tooling, prompt engineering, RAG, or agent frameworks through work,
coursework, or personal projects.
- Internship or early-career experience in fintech or other regulated environments.
- Contributions to open-source projects, hackathons, or side projects related to AI or developer
tooling.
- Depending on factors such as business unit requirements, the nature of the position, cost and applicable laws, American Express may provide visa sponsorship for certain positions.
- Contribute to the design and implementation of LLM-powered and agentic product features.
- Build and extend agentic AI workflows that reason over context, call tools, and perform actions
under guidance from senior engineers.
- Help implement and maintain retrieval-augmented generation (RAG) pipelines over financial data,
with an emphasis on correctness and safety.
- Contribute to shared AI infrastructure such as LLM services, orchestration components, and
evaluation or monitoring tooling.
- Participate in operating AI systems in production, including monitoring, debugging, and improving
reliability and performance.
- Collaborate closely with product and design partners, learning to translate customer needs into
technical solutions.
Core engineering stack
- Languages: Python, Go, TypeScript.
- Cloud and infrastructure: AWS and/or GCP, Kubernetes.
- APIs and services: REST, gRPC.
- Distributed systems: event-driven architectures, including Kafka.
Agentic AI and ML
- Commercial and open-source LLMs integrated into agentic workflows.
- Tooling for agent orchestration, retrieval-augmented generation, vector storage, and evaluation
- Schema validation and structured data handling.
AI-assisted development
- Use of AI-assisted and agentic development tools for design, implementation, testing, debugging,
and refactoring.
- Learning how to apply these tools responsibly while maintaining production-quality standards.
- All systems are built to meet high standards for reliability, security, and auditability, reflecting the
responsibility of deploying autonomous AI in a financial services environment.
- Contribute to the design and implementation of LLM-powered and agentic product features.
- Build and extend agentic AI workflows that reason over context, call tools, and perform actions
under guidance from senior engineers.
- Help implement and maintain retrieval-augmented generation (RAG) pipelines over financial data,
with an emphasis on correctness and safety.
- Contribute to shared AI infrastructure such as LLM services, orchestration components, and
evaluation or monitoring tooling.
- Participate in operating AI systems in production, including monitoring, debugging, and improving
reliability and performance.
- Collaborate closely with product and design partners, learning to translate customer needs into
technical solutions.
Core engineering stack
- Languages: Python, Go, TypeScript.
- Cloud and infrastructure: AWS and/or GCP, Kubernetes.
- APIs and services: REST, gRPC.
- Distributed systems: event-driven architectures, including Kafka.
Agentic AI and ML
- Commercial and open-source LLMs integrated into agentic workflows.
- Tooling for agent orchestration, retrieval-augmented generation, vector storage, and evaluation
- Schema validation and structured data handling.
AI-assisted development
- Use of AI-assisted and agentic development tools for design, implementation, testing, debugging,
and refactoring.
- Learning how to apply these tools responsibly while maintaining production-quality standards.
- All systems are built to meet high standards for reliability, security, and auditability, reflecting the
responsibility of deploying autonomous AI in a financial services environment.