Senior AI Engineer II - Agentic AI

Job d:

Location:

LONDON, LONDON, United Kingdom; BURGESS HILL, WEST SUSSEX, United Kingdom Job Function:
Engineering & Architecture

Schedule:

Full time

Shift: Day Workplace:
Hybrid Career Area:
Technology Company:
American Express 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, 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.

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 a Senior AI Engineer – Agentic AI, you will be a core builder responsible for turning complex, ambiguous problems into production-grade agentic systems that operate on real financial data, serve real customers, and meet real regulatory requirements.

You will work end to end: shaping solutions with product and design, building and shipping production code, and owning what you deliver after launch. The scope of this role spans customer-facing LLM-powered features, agentic systems that automate financial workflows, and internal AI capabilities that enable other engineers to build with AI safely and efficiently.

This is not a research-only role. We are looking for engineers who are comfortable operating with autonomy, exercising sound judgment, and pushing the technical envelope within the realities of a regulated financial environment.

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 AICore engineering stack

Languages:

Python, Go, Type Script Cloud  and infrastructure: AWS and/or GCP, KubernetesAPIs and services: REST, gRPCDistributed systems: event-driven architectures, including Kafka Agentic AI and MLCommercial 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 practicesAI-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.

Responsibilities 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,…