AI Engineer III - Enterprise Architecture

American Express
Phoenix, AZ

Who this role is best for

Best suited to hands-on engineers with AI/ML experience working in regulated financial services environments.

Best fit for

  • Candidates with production AI engineering experience and a strong grasp of LLMs and agentic systems
    — “This is not a research-only role. You will write production code”
  • Individuals who thrive in regulated, customer-facing environments with high reliability and compliance standards
    — “meeting the high standards for security, explainability, reliability, and compliance required in financial services”
  • Engineers comfortable with distributed systems and cloud infrastructure, particularly AWS and GCP
    — “Cloud and infrastructure: AWS and/or GCP, Kubernetes”

Things to consider

  • The role requires a bachelor’s degree, which may be a barrier for some candidates
    — “Candidates are required to have a bachelor’s degree”
  • Strong mentorship is available, but may imply a need for junior-to-mid-level technical ownership
    — “This role offers strong mentorship and opportunities to grow your technical depth”

How to stand out

  • Highlight experience with retrieval-augmented generation (RAG) in your resume and interview responses
    — “Help implement and maintain retrieval-augmented generation (RAG) pipelines”
  • Emphasize your ability to operate AI systems in production, including monitoring and debugging
    — “Participate in operating AI systems in production, including monitoring, debugging”
  • Showcase collaborative work with product and design teams through specific examples or projects
    — “Collaborate closely with product and design partners, learning to translate customer needs into technical solutions”
  • Demonstrate familiarity with event-driven architectures and tools like Kafka
    — “Distributed systems: event-driven architectures, including Kafka”
  • Position yourself as experienced in building systems with high reliability and security standards
    — “All systems are built to meet high standards for reliability, security, and auditability”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • contribute to the design and implementation of LLM-powered and agentic product features
  • build and extend agentic AI workflows
  • implement and maintain retrieval-augmented generation (RAG) pipelines
  • contribute to shared AI infrastructure
Typical background
experience in AI engineeringbackground in machine learningknowledge of production AI systems

Skills & requirements

Required

LLM DevelopmentAgentic AI SystemsProduction AI EngineeringSecurityExplainabilityReliabilityCompliance

Preferred

Technical MentorshipTeam Collaboration

Stack & domain

LlmsAgentic SystemsProduction AI EngineeringCollaborationProblem SolvingCuriosityProactivityFinance

About the role

Original posting from American Express

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, TypeScriptCloud and infrastructure: AWS and/or GCP, KubernetesAPIs and services: REST, gRPCDistributed systems: event-driven architectures, including KafkaAgentic AI and ML                                                 

Commercial and open-source LLMs integrated into agentic workflowsTooling for agent orchestration, retrieval-augmented generation, vector storage, and evaluationSchema validation and structured data handling 

AI-assisted development

Use of AI-assisted and agentic development tools for design, implementation, testing, debugging, and refactoringLearning how to apply these tools responsibly while maintaining production-quality standardsAll 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

2+ 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.Candidates are required to have a bachelor’s degree 

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.

Depending on factors such as business unit requirements, the nature of the position, cost and applicable laws, American Express may provide visa sponsorship for certain positions.

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 our 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.

Source: American Express careers

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