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Agentic AI Engineer - Global Infrastructure

Job in Fort Lauderdale, Broward County, Florida, 33338, USA
Listing for: American Express
Full Time position
Listed on 2026-10-08
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Engineering, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 89250 - 150250 USD Yearly USD 89250.00 150250.00 YEAR
Job Description & How to Apply Below
Job d:

Location:

New York, NY, United States;
Phoenix, AZ, United States;
Sunrise, FL, United States Salary: $89250 - $150250 annually + bonus + benefits

Job Function:
Engineering & Architecture

Schedule:

Full time

Shift: Day Workplace:
Hybrid Career Area:
Technology Company:
American Express Description 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.

This AI Engineer II will build and optimize trained AI/ML models, enhance data pipelines for scalability, support model integration with production systems, and ensure adherence to enterprise AI standards while collaborating cross-functionally to refine AI strategies.

Responsibilities Develops and optimizes AI/ML models, ensuring seamless integration with production environments

Builds and enhances data pipelines to support scalable and efficient AI processing

Participates in designing and reviewing AI architectures, ensuring alignment with enterprise standards

Implements model monitoring and evaluation techniques to improve AI system performance over time Ensures AI solutions adhere to governance, security, and compliance requirements

Provides support and troubleshooting for AI models and data processing pipelines in production

Collaborates effectively with teams in product and the business to align technology initiatives with business objectives

Performs standard tasks within established procedures and guidelines; works within established guidelines with some degree of independence for routine tasks

Develops and integrates components of production AI systems, including ML models or LLM-based services, with moderate independence

Contributes to AI capabilities such as model training pipelines, inference services, and retrieval workflows, improving performance and reliability

Applies enterprise standards for observability, safety, and compliance in implemented AI components 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

Knowledge of natural language processing techniques like fuzzy wuzzy and models such as BERT, Transformer models, and their real-world applications

Working knowledge of machine learning techniques and model evaluation approaches

Understanding of modern AI architectures including LLM integration patterns, retrieval-augmented generation (RAG), and basic orchestration concepts

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 or RExperience 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…
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