Sr AI Engineer I - Global Commercial Services

American Express; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

American Express in the United States seeks a Senior Software Engineer – Agentic AI to drive production-grade AI initiatives that power intelligent customer and enterprise experiences. You will work hands-on with senior engineers, architects, Product, UX, and Data Science to design, implement, and operate scalable, secure AI solutions.

This role blends strong software fundamentals with practical AI workflows.

Qualifications

• 6+ years of experience building large-scale backend or distributed software systems.
• Experience developing AI-powered applications using LLMs, agentic workflows, RAG, or modern ML platforms.
• Experience building production services using TypeScript, Go, Python or similar languages.
• Strong software engineering fundamentals across backend development, APIs, cloud infrastructure, and distributed systems.

Responsibilities

• Design, build, test, and operate production-grade agentic AI applications and services.
• Contribute to the design and implementation of shared agentic AI capabilities, including frameworks and orchestration.
• Evaluate emerging AI technologies and help incorporate practical improvements into our platform.
• Mentor junior engineers and contribute to a collaborative engineering culture.
• Collaborate with Product, UX, and cross-functional partners to deliver AI-powered capabilities from concept through production.

Skills

Go

TypeScript

Python

REST

gRPC

tRPC

AWS

GCP

Kubernetes

Distributed systems

RAG

LLM integration

Tools

VercelAI SDK

LangChain

LangGraph

LlamaIndex

Temporal

DBOS

Kafka

Zod

Job description

The Role
As a Senior Software Engineer – Agentic AI, you will be a hands-on engineer within Amex Technology, building and evolving production-grade agentic AI systems that power intelligent customer and enterprise experiences. Working closely with senior engineers, architects, Product, UX, Data Science, and Engineering teams, you will design, implement, and operate scalable, reliable, and secure AI solutions. This role combines strong software engineering fundamentals with experience building AI-powered applications.

Job Description
Senior Software Engineer I – Agentic AI
The Role
As a Senior Software Engineer – Agentic AI, you will be a hands-on engineer within Amex Technology, building and evolving production-grade agentic AI systems that power intelligent customer and enterprise experiences. Working closely with senior engineers, architects, Product, UX, Data Science, and Engineering teams, you will design, implement, and operate scalable, reliable, and secure AI solutions. This role combines strong software engineering fundamentals with experience building AI-powered applications.
Global Commercial Services (GCS) serves millions of business customers around the world, from mom-and-pop shops to Fortune 500 companies. We back businesses so they can do more business, with a mission to be the undisputed leader in financial and membership services - responsibly driving double-digit revenue growth. We do that by offering a diverse range of payment and cashflow tools, from a wide range of traditional card products, to working capital and supply chain financing, to new digital solutions that make it easy for our customers to manage a full range of their financial and payment needs.
Responsibilities
What You'll Do

• Design, build, test, and operate production-grade agentic AI applications and services.
• Contribute to the design and implementation of shared agentic AI capabilities, including:
• Agent frameworks and orchestration
• Planning, tool use, and memory strategies
• Retrieval-Augmented Generation (RAG) pipelines
• LLM integration and inference services
• Evaluation, observability, and safety tooling
• Partner with senior engineers to design scalable, reliable, and maintainable distributed systems.
• Participate in technical design discussions and code reviews, helping improve engineering quality across the team.
• Collaborate with Product, UX, and cross-functional partners to deliver AI-powered capabilities from concept through production.
• Evaluate emerging AI technologies and help incorporate practical improvements into our platform.
• Mentor junior engineers and contribute to a collaborative engineering culture.
  

Technical Environment
We don't hire to a narrow checklist, but successful candidates should be comfortable working in a modern, cloud-native engineering environment with an emphasis on agentic AI.
Core Engineering Stack

• Languages: Go, TypeScript, Python
• APIs: REST, gRPC , and tRPC
• Cloud: AWS and/or GCP
• SNS, SQS, Lambda, EKS, API Gateway
• Kubernetes
• Distributed systems and event-driven architectures (Kafka)
• Durable Execution frameworks, like Temporal or DBOS
• Orchestration frameworks such as LangGraph , LangChain , Airflow, or similar
  

Agentic AI and ML

• Integrating commercial and open-source LLMs into production applications
• Agent and orchestration frameworks such as VercelAI SDK, LangChain , LangGraph , LlamaIndex , etc.
• Retrieval-Augmented Generation (RAG) architectures
• Embedding Models and Vector Databases
• Multi-agent orchestration and agent harness development
• Prompt engineering and structured output generation
• Model serving, embeddings, and inference tooling
• Familiarity with Effect TS library
• Schema validation and state management using tools such as Zod (TypeScript)
• Emphasize evaluation, observability, safety, and reliability to support AI solutions deployed in a regulated, customer-facing environment.
  

Qualifications
What We\'re Looking For

• 6+ years of experience building large-scale backend or distributed software systems.
• Experience developing AI-powered applications using LLMs, agentic workflows, RAG, or modern ML platforms.
• Experience building production services using TypeScript, Go, Python or similar languages.
• Strong software engineering fundamentals across backend development, APIs, cloud infrastructure, and distributed systems.
• Familiarity with cloud platforms, containers, and Kubernetes.
• Experience with asynchronous processing, workflow engines, queues, or streaming systems.
• Strong problem-solving skills and the ability to work through ambiguous technical challenges.
• Excellent collaboration and communication skills, with the ability to work effectively across engineering and product teams.
• Passion for learning new technologies and contributing to engineering best practices.
  

Preferred Qualifications
Preferred Qualifications

• Experience building AI applications in financial services or other regulated industries.
• Experience deploying production LLM or RAG-based systems.
• Familiarity with evaluation frameworks, observability, and AI safety practices.
• Contributions to open-source software or AI-related projects.
• Experience with fine-tuning, model optimization, or inference pipelines is a plus.