Drimva

American Express

Agentic AI Engineer - Core Platforms

New York, NY +2 · Hybrid · Full-time · Posted Oct 14, 2026

Location
New York, NY
Phoenix, AZ
Sunrise, FL
Experience
2+ years of software development, including hands-on experience in machine learning, AI technologies, and Agentic AI solutions.
Education
Bachelor's degree in Computer Science, Machine Learning, Data Science, and/or comparable experience; advanced degree preferred.
Visa sponsorship
Employment eligibility to work with American Express in the United States is required; the company will not pursue visa sponsorship.

About the job

Implements, deploys, and supports AI/ML models and LLM-based services in approved GPU-enabled environments, following enterprise security, governance, and operational standards.

What you'll do

  • Packages, validates, versions, deploys, monitors, and supports rollback for AI models and production pipelines.
  • Contributes to CI/CD, container, Kubernetes, registry, testing, and telemetry configurations; troubleshoots production issues.
  • Collaborates with product and business teams and ensures AI implementations meet governance, security, compliance, observability, and safety standards.

What they ask for

  • 2+ years of software development, including hands-on experience in machine learning, AI technologies, and Agentic AI solutions.
  • Knowledge of Python and data processing technologies; working knowledge of machine learning techniques and model evaluation.
  • Foundational working knowledge of MLOps or LLMOps, containers, Kubernetes fundamentals, CI/CD, artifact management, testing, and monitoring.
  • Employment eligibility to work with American Express in the United States; the company will not pursue visa sponsorship.

Nice to have

  • Advanced degree preferred.
  • Experience with LLMs, such as GPT-3.5/4 or similar AI models.

Pay

USD 89250 - 150250 annually (base salary)

Tools

Python, R, GPT-3.5/4, Kubernetes, CI/CD, GPU

AI focus

Operationalizes production AI/ML models and LLM-based services, including monitoring and evaluation, deployment pipelines, validation, versioning, and rollback.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)