Sr AI Engineer II-Global Servicing Tech

Sr AI Engineer II-Global Servicing Tech

Sunrise, FL, United States

** Job Description*
* 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.

** The Role*
* 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.

** 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, 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, Type Script

+ 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.

** Qualifications*
* + 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…