Drimva

American Express

Sr Agentic AI Engineer - Core Platforms

New York, NY +2 · Hybrid · Senior · Full-time · Posted Oct 19, 2026

Location
New York, NY
Phoenix, AZ
Sunrise, FL
Experience
5+ years of software development experience, 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 for these positions.

About the job

Designs, optimizes, and operates production inference services and AI systems, integrating models into enterprise platforms while meeting performance, reliability, security, and compliance standards.

What you'll do

  • Design and operate scalable inference services; optimize latency, throughput, accelerator utilization, and cost.
  • Build and maintain end-to-end machine learning operations pipelines for model deployment, monitoring, and maintenance.
  • Partner with cross-functional teams and mentor engineers on production AI systems and enterprise standards.

What they ask for

  • Strong knowledge of production model serving, inference optimization, GPU fundamentals, Kubernetes, APIs, and distributed systems.
  • Experience with LLMs, model-serving frameworks, containerized GPU workloads, and performance or reliability optimization.
  • Experience deploying AI models and pipelines, including continuous integration/continuous deployment pipelines and containerized deployments.
  • Employment eligibility to work with American Express in the United States; the company will not pursue visa sponsorship.

Nice to have

  • Advanced degree.
  • Experience with languages such as Python, R, Java, or C++.

Pay

USD 123000 - 215250 annually + bonus + benefits (base salary)

Tools

GPT-3.5/4, Python, R, Java, C++, Kubernetes

AI focus

Production inference and serving for AI, machine learning, LLMs, and Agentic AI; model deployment, optimization, and operations.

Model-written summary · the original posting is authoritative

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