Senior Agentic AI Engineer II - Global Infrastructure

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.

The Sr. AI Engineer II leads the development of advanced AI/machine learning frameworks and innovative natural language processing models, translating complex business needs into scalable models, optimizing Big Data pipelines, ensuring compliance, and foster growth of individuals on the team.

Qualifications

• Education and Knowledge
• Bachelor's degree in Computer Science, Machine Learning, Data Science, and/or comparable experience; advanced degree preferred
• Knowledge of Python and data processing technologies such as Big Data (Hadoop, Spark)
• Knowledge of natural language processing techniques like fuzzy wuzzy and models such as BERT, Transformer models, and their real-world applications
• Deep expertise in machine learning, including tradeoffs in model selection, evaluation, and optimization
• Expert-level understanding of modern AI architectures, including LLM systems, agentic workflows, retrieval strategies, and scalable orchestration patterns
• Work Experience
• Experience in software development with a focus on machine learning, generative AI, Big Data, and prompt engineering
• Experience in working with large language models (LLMs), especially GPT-3.5/4 or similar AI models
• Experience in languages such as Python, R, Java, or C++
• Experience in deploying AI models and pipelines using machine leanring operations tools
• Experience in machine learning algorithms and experience applying them to real-world problems
• Experience in continuous integration/continuous deployment pipelines and containerized deployments
• Experience in building and maintaining data pipelines and extract, transform, and load processes
• Extensive experience architecting and deploying large-scale AI systems in production environments
• Experience leading development of distributed AI platforms, real-time inference systems, and cloud-native AI services
• Advanced expertise in a technical domain, and moderate expertise across several different domains