Senior AI Engineer I

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, platforms, and services 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 colleagues. 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. What You’ll Do Design, build, and ship LLM-powered and agentic product features that change how customers manage their finances. Build agentic AI systems that reason over context, invoke tools, take real actions, and recover gracefully from failure. Architect and implement production-grade RAG pipelines over sensitive financial data, with strict requirements for correctness, auditability, and safety. Contribute to shared AI infrastructure, including LLM services, agent orchestration frameworks, and evaluation and monitoring tooling, that scales agentic development across Amex Technology. Own the systems you build in production, including reliability, latency, cost, and failure modes. Work closely with product and design partners; engineers in this role are expected to think in terms of customer outcomes, not just technical execution. Technical Environment We don’t hire to a narrow checklist, but candidates should be comfortable operating in a modern, enterprise-scale environment with a strong emphasis 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 Strong schema, validation, and state management practices AI-assisted development Fluency with AI-assisted and agentic development workflows for design, implementation, testing, debugging, and refactoring Thoughtful use of these tools while maintaining production-quality engineering 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. What We’re Looking For 5+ years of software engineering experience, including meaningful production experience with LLMs or applied ML systems. A track record of shipping AI-powered or agentic systems that real users depend on. Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure. Hands-on experience with modern LLM tooling and agentic patterns and architectures. Fluency with AI-assisted and agentic development workflows. Strong sense of ownership and sound technical judgment. Comfort operating with ambiguity and turning it into shipped reliable product. A strong product mindset and customer orientation. 9+ Experience building agentic systems in fintech or other regulated industries. Experience as a founding engineer or early technical contributor in high-growth environments. Demonstrated ability to ship technically complex systems in regulated contexts that customers actively rely on. Meaningful open-source contributions, particularly in AI or developer tooling.