AI Engineer III
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 this 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.
Joining Amex Tech means discovering and shaping your contribution to something big. Here, you can work alongside talented tech teams and build a unique career with the Powerful Backing of American Express. With a range of opportunities to work with the latest technologies, and a commitment to back the broader engineering community through open source, our mission is to power your success. Because Amex Tech is powered by our technology, our culture, and our colleagues.
The Technology organization enables and accelerates the company’s growth strategies, delivering global capabilities and services in support of Amex’s customers and colleagues, while maintaining 24/7 servicing and availability to ensure an uninterrupted, high-quality customer experience. Technology provides the foundation for everything we do in the company while driving differentiation through building and leveraging innovative technology and data insights.
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.
What You’ll Do
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.
Technical Environment
We don’t hire toa narrow checklist, but candidates should be excited to grow in a modern, enterprise-scale engineering environment with a focus on agentic AI.
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.
4+ 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.
Preferred Qualifications
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.