American Express—AI Engineer II

Job description

Description: 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. 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 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. Requirements: - 3–5+ years of experience in full stack -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 Responsibilities: - 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.