AI Platform Engineer: Build Scalable, Production AI

Global Payments; United States; On-site; USD 130,000 - 190,000; Full time

Job summary

Global Payments seeks an AI Platform Engineer to advance scalable AI platform capabilities, enabling teams to train, deploy, monitor and scale AI/ML solutions securely and efficiently. You will drive automated deployment, data pipelines and observability to accelerate from experimentation to production with cost awareness.

The role focuses on building model serving, APIs, prompt/RAG workflows, and scalable cloud infrastructure to support a global organization and diverse data teams.

Qualifications

• 4 to 8 years of hands-on experience building and operating AI platforms.
• Proficiency in Python, SQL, cloud services, Docker, Kubernetes, CI/CD, and IaC (Terraform).
• Experience with MLOps, LLMOps, MLflow, APIs, monitoring, and production troubleshooting.

Responsibilities

• Build and evolve scalable AI platform capabilities for training, deploying, monitoring and scaling AI solutions.
• Create automated model deployment, data/feature pipelines, evaluation workflows, and CI/CD capabilities.
• Strengthen production AI reliability via observability, model monitoring, logging and troubleshooting.
• Shape model serving, APIs, prompts, and Retrieval-Augmented Generation workflows for new AI-powered experiences.

Skills

Python

SQL

Cloud services

Docker

Kubernetes

CI/CD

Terraform

MLflow

LLMOps

APIs

Monitoring

Education

Bachelor's degree in a quantitative field

Master's degree in data science or related

Tools

Spark

Power BI

Tableau

Hadoop

Job description

Global Payments seeks an AI Platform Engineer to advance scalable AI platform capabilities, enabling teams to train, deploy, monitor and scale AI/ML solutions securely and efficiently. You will drive automated deployment, data pipelines and observability to accelerate from experimentation to production with cost awareness.

The role focuses on building model serving, APIs, prompt/RAG workflows, and scalable cloud infrastructure to support a global organization and diverse data teams.