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, platforms, and services 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 colleagues. 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.
As an AI Engineer III, 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.
- 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.
- Bachelor’s degree in technology related discipline or equivalent experience preferred.
- 6-8 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.