Senior Agentic AI Engineer - Core Platforms

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 Evaluation Engineer designs, develops, and maintains evaluation frameworks for AI and machine learning solutions, including LLM, RAG, agentic, and multimodal applications. This role translates business, product, risk, and governance requirements into measurable success criteria; builds automated and human-in-the-loop evaluation pipelines; and partners with cross-functional teams to ensure AI systems meet enterprise standards for quality, safety, reliability, compliance, latency, and cost.

Education and Knowledge

- 5+ years' Experience in software development, including hands on experience in machine learning, AI Technologies, and Agentic solutions
- 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
- Advanced knowledge of machine learning techniques and performance optimization
- Strong understanding of AI system architectures including LLM ecosystems, retrieval systems, orchestration frameworks, and evaluation methodologies

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
- Experience delivering end-to-end AI systems in production, including design and operational ownership
- Experience with distributed systems design, scalable APIs, and cloud-native AI infrastructure, including monitoring and optimization
- Advanced expertise in a technical domain and moderate expertise in a new, different technical domain
- Experience building evaluation harnesses and automated test pipelines for LLM, RAG, or agentic applications using production-representative datasets.
- Experience designing human-in-the-loop and model-based evaluation workflows, including calibration, error analysis, and validation of evaluation quality.
- Experience integrating evaluation results into CI/CD, release readiness, production monitoring, and governance evidence.

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.