Agentic AI Engineer - Core Platforms

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.

The Implementation / ML Ops Engineer is responsible for implementing, deploying, and supporting AI/ML models within approved GPU-enabled environments. This role packages and operationalizes trained models, supports scalable data and deployment pipelines, integrates models with production systems, and helps maintain reliable monitoring, validation, versioning, and rollback processes. The engineer works within established enterprise patterns, security controls, and AI governance standards while collaborating with product, technology, and business partners to deliver production-ready AI capabilities.

Responsibilities 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

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

Implements and supports model packaging, validation, versioning, deployment, monitoring, and rollback using approved templates and controls.

Contributes to CI/CD, container, Kubernetes, registry, testing, and telemetry configurations for assigned workloads.

Troubleshoots common implementation issues and escalates complex design, optimization, or production problems to senior engineers. Qualifications Education and Knowledge2+ years software development, including hands-on experience in machine learning, AI technologies, and Agentic AI 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

Working knowledge of machine learning techniques and model evaluation approaches

Foundational working knowledge of MLOps or LLMOps, containers, Kubernetes fundamentals, CI/CD, artifact management, testing, and monitoring.

Basic understanding of GPU resource needs, runtime dependencies, scheduling constraints, and enterprise security and change controls.

Work Experience Experience in working with large language models (LLMs), especially GPT-3.5/4 or similar AI models

Experience in languages such as Python or…