AI & Data Platform Engineer

Global Payments Inc.; Alpharetta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Global Payments Inc. is seeking an AI Platform Engineer to join the Data & AI team and help shape the future of global commerce.

You’ll build and evolve secure, scalable AI platform capabilities that enable data scientists, machine learning engineers and application teams to move AI solutions from experimentation to production with confidence. You’ll deploy models, establish observability, automation and CI/CD, and pioneer generative AI workflows and cost optimization across a globally

Qualifications

• 4–8 years of hands-on experience building, deploying, or operating AI/ML platforms in production.
• Strong engineering capabilities with Python, SQL, cloud services, Docker, Kubernetes, CI/CD and infrastructure as code (Terraform or equivalent).
• Experience with MLOps, LLMOps, model lifecycle tooling, APIs, monitoring and debugging in production.

Responsibilities

• Build and evolve scalable AI platform capabilities to train, deploy, monitor and scale AI/ML solutions securely and efficiently.
• Automate model deployment, data/feature pipelines, evaluation workflows and CI/CD for faster production delivery.
• Improve observability, logging and model monitoring to maintain performance and reliability at scale.
• Advance generative AI workflows, model serving and vector infrastructure to enable new AI-powered experiences.
• Influence platform architecture, cloud infrastructure and engineering standards for cost effectiveness and resilience.

Skills

Python

SQL

Cloud services

Docker

Kubernetes

CI/CD

Infrastructure as code

MLOps

LLMOps

APIs

Monitoring

Education

Bachelor's degree in quantitative analytics / statistics / mathematics / data science

Tools

MLflow

Terraform

Job description

Ready to take your career global?

Make your mark at one of the biggest names in payments. We’re looking for an AI Platform Engineer to join our ever evolving Data & AI team and help shape the future of global commerce. You’ll build and evolve the secure, scalable AI platform capabilities that enable data scientists, machine learning engineers and application teams to move AI solutions from experimentation to production with confidence. From model deployment and observability to automation, generative AI workflows and cost optimization, your work will directly influence how quickly and reliably Global Payments can turn AI innovation into real business and client impact. You’ll have the opportunity to shape how AI is engineered and scaled across a global organization while helping build the technology foundation for the future of payments.

What you’ll own

• Build and evolve scalable AI platform capabilities that enable teams to train, deploy, monitor and scale artificial intelligence and machine learning solutions reliably, securely and efficiently.
• Accelerate AI delivery from experimentation to production by creating automated model deployment, data and feature pipelines, evaluation workflows and continuous integration and continuous delivery (CI/CD) capabilities that improve speed, consistency and quality.
• Strengthen the reliability of production AI through robust observability, model monitoring, logging and evaluation capabilities that help teams identify issues faster, maintain performance and confidently operate AI at scale.
• Shape the foundation for generative AI innovation by advancing model serving, application programming interfaces (APIs), prompt and Retrieval-Augmented Generation (RAG) workflows and vector infrastructure that enable teams to build new AI-powered experiences.
• Optimize the performance and economics of AI at scale by influencing platform architecture, cloud infrastructure and engineering standards that improve efficiency, security, resilience and cost effectiveness.

What you’ll bring

• 4 to 8 years of hands‑on experience building, automating, deploying or operating AI and machine learning platforms, with demonstrated success supporting production environments.
• Strong engineering capabilities with Python, Structured Query Language (SQL), cloud services, Docker, Kubernetes, CI/CD and infrastructure as code, using technologies such as Terraform or equivalent solutions.
• Proven experience with machine learning operations (MLOps), large language model operations (LLMOps), model lifecycle tooling such as MLflow, model serving, APIs, monitoring, logging and production troubleshooting.
• Experience designing and operating data pipelines, distributed processing and scalable cloud-based architectures, with the judgment to solve complex technical challenges and improve platform reliability.
• A relevant degree in quantitative analytics, statistics, mathematics, data science or a related discipline, combined with a collaborative and innovative mindset and the ability to influence technical decisions across teams.

It’s a bonus if you have

• Experience with product analytics and using data and insights to influence product or platform decisions.
• A master’s degree in quantitative analytics, statistics, mathematics, data science or a related discipline.
• Experience with analytics, distributed data or visualization technologies such as Spark, Hadoop, Power BI, Tableau or similar platforms.

About The Team

Our inclusive and global teams win together every day. We’re proud to have the best minds in the industry, who you can learn from as you grow your career. The people, the energy, the connections — it’s unmatched. Come and be part of an ever-evolving company and get dynamic opportunities that go beyond borders.

What makes a Globalpayer?

Globalpayers think like a client, act like an owner and win as one team. We’re curious and innovative — always finding better ways to deliver impact. We empower each other to make decisions, and it’s our passion that drives excellence in everything we set out to do.

Come and be part of an ever-evolving company and get dynamic opportunities that go beyond borders.

Does this sound like you? Then you sound like a Globalpayer.