Drimva

American Express

Sr AI Engineer I - Global Servicing Technology

Sunrise, FL · Hybrid · Senior · Full-time · Posted Jul 20, 2026

Experience
7+ years in software engineering, machine learning, or applied AI, including building production systems.
Visa sponsorship
Employment eligibility to work with American Express in the United States is required; the company will not pursue visa sponsorship for these positions.

About the job

Builds and operates AI capabilities for American Express’s Case Management Platform, improving dispute and fraud servicing through automation, decision support, and connected enterprise data.

What you'll do

  • Design, build, deploy, and improve scalable AI and agentic systems, including LLM apps, RAG systems, and personalization features.
  • Develop intelligent workflows, monitoring, quality checks, and shared AI platforms for dispute and fraud servicing.
  • Partner with product, engineering, and business teams while ensuring AI systems meet enterprise security, compliance, reliability, and governance standards.

What they ask for

  • 7+ years of experience in software engineering, machine learning, or applied AI, including building production systems.
  • Experience with agentic AI systems, RAG, vector databases, and the LLM lifecycle.
  • Strong Python skills and experience building backend services, APIs, and data pipelines.
  • Hands-on experience with LLMs, GenAI, or applied machine learning in real-world products; experience with GCP and scalable cloud-native solutions.

Nice to have

  • Experience with case management platforms, customer data systems, or regulated industries.
  • Experience with Docker, Kubernetes, AI governance, model risk management, or responsible AI.

Pay

$123000 - $215250 annually (USD, base salary)

Tools

Python, LangChain, LangGraph, PyTorch, TensorFlow, Scikit-learn, Google Cloud Platform (GCP), BigQuery

AI focus

Develops production AI and agentic systems, LLM and RAG applications, intelligent workflows, automation, monitoring, and shared AI platforms, with emphasis on responsible, governed deployment.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)