AI Platform Engineer Jobs in Georgia
AI Platform Engineer jobs in Georgia are in strong and growing demand, concentrated in enterprise technology, financial services, supply chain logistics, and government contracting, with openings from early-career engineers through principal and staff-level architects. Atlanta is the dominant hiring center, with meaningful activity also in Alpharetta and Savannah, where established employers like NCR Voyix, The Home Depot, and Fiserv maintain large technology operations. The most in-demand specialties across Georgia postings include MLOps infrastructure, large language model deployment pipelines, and cloud-native platform engineering on AWS and Google Cloud. Find a role that fits below and apply directly.
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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. Apply now to take your career global.
EEOC Statement
Global Payments is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here.
If you are made a conditional offer of employment and will be working in the United States, you will be required to undergo a drug test. In developing this job description care was taken to include all competencies and requirements needed to successfully perform the position. Reasonable accommodations will be provided for individuals with qualified disabilities both during the hiring process, as well as to allow the individual to perform the essential functions of the job, if hired.
Washington Candidates: Click here for information on the Fair Chance Act.
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. Apply now to take your career global.
EEOC Statement
Global Payments is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here.
If you are made a conditional offer of employment and will be working in the United States, you will be required to undergo a drug test. In developing this job description care was taken to include all competencies and requirements needed to successfully perform the position. Reasonable accommodations will be provided for individuals with qualified disabilities both during the hiring process, as well as to allow the individual to perform the essential functions of the job, if hired.
Washington Candidates: Click here for information on the Fair Chance Act.
See All 31 AI Platform Engineer Jobs in Georgia
Find roles in Georgia that match your experience and apply in just a few clicks.
Find AI Platform Engineer JobsAI Platform Engineer Jobs by City in Georgia
Where Georgia roles are concentrated, by current openings.
AI Platform Engineer Job Market in Georgia
A snapshot from current Georgia openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Investment & Asset Management
What Georgia Employers Look For
The qualifications that appear most often in AI platform engineer jobs across Georgia.
- Bachelor's or master's degree in computer science, software engineering, or a related field
- Hands-on experience building and maintaining ML or AI infrastructure on AWS, Azure, or Google Cloud
- Proficiency with MLOps tooling such as Kubeflow, MLflow, Ray, or equivalent orchestration platforms
- Strong programming ability in Python and familiarity with containerization using Docker and Kubernetes
- Experience integrating large language models or generative AI components into production systems
- Ability to collaborate with data science and software engineering teams on end-to-end model deployment
AI Platform Engineer Jobs in Georgia: Frequently Asked Questions
How do you become a ai platform engineer in Georgia?
The most direct path is a bachelor's degree in computer science, software engineering, or a related technical discipline, followed by hands-on experience with cloud infrastructure and ML tooling. Georgia has no state-issued license for this role, so employers evaluate candidates on demonstrated skills. Building a portfolio that shows production-grade MLOps work, contributing to open-source AI infrastructure projects, and earning cloud certifications from AWS or Google Cloud significantly strengthens a Georgia candidacy.
How much do AI platform engineers make in Georgia?
AI platform engineers in Georgia earn a median of about $104,610 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $60,920 for the lowest 10% to over $173,060 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai platform engineers in Georgia?
Employers hiring ai platform engineers in Georgia right now include Intercontinental Exchange, Invesco, and Capgemini, based on current listings on Migrate Mate as of November 2026. Georgia's dense concentration of Fortune 500 headquarters and major fintech and logistics companies means demand is distributed across both large enterprises and high-growth technology firms based in and around Atlanta.
Which Georgia cities have the most ai platform engineer jobs?
Atlanta, Alpharetta, and Warner Robins have the most ai platform engineer openings in Georgia. Atlanta drives the largest share because it hosts the regional headquarters of major enterprises in financial technology, retail technology, and government contracting, while Alpharetta's technology corridor is home to dozens of software and data companies that run their own AI platform teams.
Are there remote ai platform engineer jobs in Georgia?
Yes, and more than most fields. About 85% of ai platform engineer openings tied to Georgia are remote or hybrid as of November 2026, reflecting how much of the work happens through cloud consoles, version control systems, and collaborative tooling rather than on-site infrastructure. The portions of the role most likely to remain fully remote are pipeline development, model monitoring, and MLOps configuration work.
How can I get hired as a ai platform engineer in Georgia with little or no experience?
The most realistic entry point is a junior or associate platform engineer role at one of Georgia's large enterprise technology employers, where structured rotational programs or associate engineer tracks exist for recent graduates. Georgia Tech's strong computer science and machine learning programs feed directly into early-career pipelines at Atlanta-area companies. Lateral entry from a software engineering, data engineering, or DevOps background is common, and building a public portfolio of MLOps or cloud infrastructure projects closes experience gaps faster than additional coursework alone.
Where can I find and apply to ai platform engineer jobs in Georgia?
You can find and apply to ai platform engineer jobs in Georgia on Migrate Mate, which lists current Georgia openings updated regularly. Search the listings, find roles that match your experience and preferred location or remote arrangement, and apply directly to the employers posting them.
See All 31 AI Platform Engineer Jobs in Georgia
Find roles in Georgia that match your experience and apply in just a few clicks.
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