AI Engineer III - Enterprise Architecture at American Express in Phoenix, AZ

  • Company: American Express
  • Location: Phoenix, AZ, United States
  • Job type: full time
  • Workplace: onsite
  • Posted: 2026-10-13

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Job description

The Enterprise Technology Services organization partners with every part of the American Express business to power the company's growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, paltforms and sercices globally. Specifically, our team is responsible for the company's technology engineering, architecture, and infrastructure, providing 24X7 support to ensure an uninterrupted, high quality experience for customers and colleague. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company. At American Express, AI is reshaping the future of commerce and refining 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 The Role 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. 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 to a 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

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