> Markdown version of [/jobs/ext/4428769-agentic-ai-engineer-core-platforms](https://www.wearedevelopers.com/jobs/ext/4428769-agentic-ai-engineer-core-platforms). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Agentic AI Engineer - Core Platforms - **Company:** American Express Company - **Location:** New York, NY, United States - **Experience:** Experienced - **Salary:** $89,250.0 - $150,250.0 - **Contract:** Internship / Graduate position - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, Continuous Delivery, Continuous Integration, Distributed Systems, Python (Programming Language), Machine Learning, Software Engineering, Management of Software Versions, Working Model 2D, Data Processing, Cloud Platform System, Delivery Pipeline, Large Language Models, Model Validation, Agentic-AI, Containerization, Kubernetes, Information Technology, Machine Learning Operations, GPT - **Published:** October 13, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=dbf6dabf0ac3dff1 ## About the Role * 2+ 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 R * Experience in deploying AI models and pipelines using machine learning operations tools * Experience in continuous integration/continuous deployment pipelines and containerized deployments * Experience developing and deploying machine learning or LLM-enabled applications in production or near-production environments * Practical experience with distributed systems concepts, APIs, and cloud-native infrastructure supporting AI workloads * Moderate expertise in a specific technical domain * Some practical experience contributing to software, infrastructure, container, data, or machine learning deployment and automation work. Exposure through project, internship, or practical work to containerized deployment, artifact repositories, automated testing, monitoring, versioning, or rollback. * Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions. ## Description 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., We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually. US Job Seekers - Click to view the " Know Your Rights " poster. If the link does not work, you may access the poster by copying and pasting the following URL in a new browser window: https://www.eeoc.gov/poster.