AI Engineer 2

Introducing Amex Tech & Enterprise CRM Solutions (eCRMs)

At American Express, technology is at the core of how we innovate, grow, and deliver exceptional customer experiences. Joining Amex Tech means being part of a global engineering organization that is shaping the future of commerce through cutting-edge platforms, data, and Artificial Intelligence. Our teams build scalable, secure, and intelligent systems that power seamless experiences for customers and colleagues worldwide.

Within this ecosystem, Enterprise CRM Solutions (eCRMs), part of the International Card & Risk Services Technology organization, plays a pivotal role in enabling customer-centric growth. eCRMs brings together engineering, product, and business teams to deliver modern, connected CRM capabilities across both Customer and Sales domains. The organization is focused on transforming the CRM landscape by centralizing customer data, reducing fragmentation, and enabling more personalized, insight-driven interactions at scale.

Artificial Intelligence is a key driver of this transformation. From intelligent automation to advanced decisioning and personalized engagement, we are embedding AI into core sales and customer platforms—while ensuring strong governance, reliability, and responsible use at enterprise scale.

Role Description

As an AI Engineer within Enterprise CRM Solutions (eCRMs), you will contribute to advancing AI-driven transformation across customer and sales platforms at American Express. Working at the intersection of data, AI, and CRM modernization, you will help build intelligent, scalable solutions that enhance customer engagement, improve sales effectiveness, and support compliance and governance.

In this role, you will develop and implement AI-powered capabilities that bring greater intelligence and automation into customer and sales processes. This includes building GenAI and Agentic AI solutions for quality monitoring, intelligent workflows, personalized customer experiences, and customer data enrichment. You will work with enterprise data platforms and cloud-native technologies to develop production-ready AI applications that integrate with business systems and enable better decision-making.

You will also contribute to the development of enterprise AI platforms, reusable frameworks, and engineering best practices while ensuring AI solutions are reliable, secure, and aligned with responsible AI and governance standards.

• 3–5+ years of experience in software engineering, machine learning engineering, data engineering, or applied AI. 
• Hands-on experience building or integrating GenAI applications using Large Language Models (LLMs). 
• Experience with Agentic AI concepts, including orchestration frameworks, tool calling, context management, or multi-step AI workflows. 
• Understanding of Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and LLM evaluation techniques. 
• Strong programming skills in Python and experience developing backend services, APIs, and data pipelines. 
• Experience with AI/ML frameworks such as LangChain, LangGraph, PyTorch, TensorFlow, or Scikit-learn. 
• Working knowledge of Google Cloud Platform (GCP), including BigQuery, Composer (Airflow), DataProc, Cloud Storage, and related data services. 
• Understanding of cloud-native application development, distributed systems, and modern software engineering practices. 
• Knowledge of CI/CD, containerization (Docker), and production deployment concepts. 
• Good problem-solving, analytical, and communication skills with the ability to work collaboratively in cross-functional teams.

• Develop and implement AI and Agentic AI solutions that enhance customer engagement, sales effectiveness, and operational efficiency across enterprise CRM platforms.  
• Build intelligent workflows using Large Language Models (LLMs), enterprise data, and tool integrations to automate customer and business processes. 
• Develop production-ready GenAI applications, including Retrieval-Augmented Generation (RAG), prompt engineering, and AI-powered business workflows. 
• Build and maintain scalable data pipelines and AI solutions using Google Cloud Platform (GCP) services such as BigQuery, Composer (Airflow), DataProc, and related cloud services. 
• Integrate AI applications with enterprise systems, APIs, and data platforms while ensuring operational reliability and performance. 
• Collaborate with product managers, software engineers, data engineers, and business stakeholders to translate business requirements into AI-enabled solutions. 
• Contribute to shared AI frameworks, reusable components, evaluation pipelines, and engineering standards. 
• Ensure AI applications comply with enterprise security, governance, responsible AI, and operational standards.