AI Engineer Visa Sponsorship Jobs in Georgia
Georgia's AI engineering market centers on Atlanta, where companies like NCR Voyix, Cox Enterprises, and Delta Air Lines have built substantial technology teams alongside a growing cohort of AI-focused startups. Georgia Tech's deep research pipeline feeds demand for AI engineers across financial services, logistics, and healthcare, making the state a consistent source of H-1B sponsorship activity.
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We create possibilities that move life and commerce forward
Welcome to Manhattan. Every day, our supply chain commerce technology connects two billion people to 20 billion consumer choices. In the warehouse, on the road and in the store, we make what was once impossible, possible. If you want to tackle complex problems and redefine markets, you’ve come to the right place.
Principal AI Engineer is a senior technical leader responsible for designing, developing, and guiding the implementation of advanced artificial intelligence systems that support business goals. They combine deep expertise in machine learning, data science, and software engineering with strategic leadership to drive AI initiatives across an organization. They will drive the adoption of AI solutions by evangelizing their value, educating stakeholders, and guiding teams to integrate scalable and responsible AI capabilities into products and business processes.
MINIMUM REQUIREMENTS –
- 7+ years of industry experience in software engineering, machine learning, or AI roles, with a focus on developing, deploying, and scaling ML/AI solutions.
- 3+ years of proven experience in designing large-scale AI systems and defining technical roadmaps.
- Strong experience developing AI-driven workflows using eknowledge platforms, and AI agent frameworks such as Microsoft Copilot, Glean, and Google Agentspace.
- Deep knowledge of:
- Machine Learning (classification, regression, clustering, recommendation systems)
- Deep Learning (CNNs, RNNs, Transformers, GANs)
- Natural Language Processing (BERT, GPT, LLM fine-tuning)
- Computer Vision (YOLO, ResNet, object tracking, OCR)
- Expertise in:
- Python and relevant ML libraries (TensorFlow, PyTorch, Scikit-learn, Hugging Face)
- Data engineering and pipeline development (Airflow, Spark, ETL systems)
- MLOps, model lifecycle management, and production-grade deployment
- Cloud platforms (AWS/GCP/Azure), containerization (Docker), orchestration (Kubernetes)
- Track record of scaling ML models from experimentation to production across teams or business units.
- Design and implement integrations using Model Context Protocol to connect AI models with external tools, APIs, and data sources.
- Demonstrated ability to set research and development direction based on business needs.
- Possesses and applies moderate to complex knowledge of particular product or platform to the completion of assignments.
- 3+ years experience interfacing and partnering with vendors.
- 3+ years experience assisting in strategy/roadmap and planning.
- Strong communication skills and ability to communicate at all levels of the organization (technical and business).
- 2+ years experience leading/mentoring more junior staff members.
- Highly self-motivated, directed, ability to work independently and be results-driven.
- 5+ years experience with SharePoint for document management and sharing.
- 5+ years experience with IT ticketing software (Quality Center, ServiceNow, JIRA).
- 3+ years experience in agile/waterfall software delivery methodologies.
- 3+ years experience using Jira, Bitbucket and Confluence agile toolsets or similar.
- 5+ years experience working with small, geographically distributed teams.
- 5+ years experience working both independently and in a team oriented, collaborative environment.
- Ability to be flexible while delivering assignments with understanding that deliverables may change based on business needs.
EDUCATION REQUIREMENTS –
- Bachelor’s degree or foreign equivalent in computer science, engineering or related field or equivalent work experience.
Principal Duties and Responsibilities –
- AI Architecture & Strategy: Design scalable AI/ML architectures and define long-term AI technology strategy aligned with business objectives.
- Model Development: Lead development of machine learning, deep learning, and generative AI models for production environments.
- Technical Leadership: Mentor AI engineers, data scientists, and ML engineers; set engineering standards and best practices.
- Research & Innovation: Evaluate emerging AI technologies and integrate cutting-edge methods into products and platforms.
- Production Deployment: Oversee model deployment, monitoring, optimization, and lifecycle management in cloud or on-prem environments.
- Cross-Functional Collaboration: Work closely with product managers, data engineers, and business stakeholders to translate requirements into AI solutions.
- Responsible AI & Governance: Ensure ethical AI practices, model explainability, fairness, privacy, and regulatory compliance.
- Performance Optimization: Improve model accuracy, efficiency, scalability, and reliability for enterprise-scale systems.
ADDITIONAL CHARACTERISTICS –
- Independently performs assignments to achieve stated objective. Determines and develops approach to solutions.
- Receives technical guidance only on unusual or complex problems or issues.
- May be responsible for entire projects having moderate to complex scope/impact or portions of projects having considerable scope/impact.
- Uses judgment and discretion to determine work priorities, receiving little instruction from others.
LI-GW1
Committed to diversity and inclusion
At Manhattan, it’s about more than just the work. From cultural celebrations to interest groups to volunteer opportunities, your true self is always welcome here. Our team members’ backgrounds, experiences and perspectives add to us as a whole and make us unique.
We are proudly an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a veteran. In the United States, Manhattan Associates participates in the Employment Eligibility Verification Program (E-Verify) operated by the Department of Homeland Security in partnership with the Social Security Administration. Participation in the E-Verify Program allows Manhattan to confirm the employment eligibility of all newly hired employees after the Employment Eligibility Verification Form (Form I-9) has been completed.

We create possibilities that move life and commerce forward
Welcome to Manhattan. Every day, our supply chain commerce technology connects two billion people to 20 billion consumer choices. In the warehouse, on the road and in the store, we make what was once impossible, possible. If you want to tackle complex problems and redefine markets, you’ve come to the right place.
Principal AI Engineer is a senior technical leader responsible for designing, developing, and guiding the implementation of advanced artificial intelligence systems that support business goals. They combine deep expertise in machine learning, data science, and software engineering with strategic leadership to drive AI initiatives across an organization. They will drive the adoption of AI solutions by evangelizing their value, educating stakeholders, and guiding teams to integrate scalable and responsible AI capabilities into products and business processes.
MINIMUM REQUIREMENTS –
- 7+ years of industry experience in software engineering, machine learning, or AI roles, with a focus on developing, deploying, and scaling ML/AI solutions.
- 3+ years of proven experience in designing large-scale AI systems and defining technical roadmaps.
- Strong experience developing AI-driven workflows using eknowledge platforms, and AI agent frameworks such as Microsoft Copilot, Glean, and Google Agentspace.
- Deep knowledge of:
- Machine Learning (classification, regression, clustering, recommendation systems)
- Deep Learning (CNNs, RNNs, Transformers, GANs)
- Natural Language Processing (BERT, GPT, LLM fine-tuning)
- Computer Vision (YOLO, ResNet, object tracking, OCR)
- Expertise in:
- Python and relevant ML libraries (TensorFlow, PyTorch, Scikit-learn, Hugging Face)
- Data engineering and pipeline development (Airflow, Spark, ETL systems)
- MLOps, model lifecycle management, and production-grade deployment
- Cloud platforms (AWS/GCP/Azure), containerization (Docker), orchestration (Kubernetes)
- Track record of scaling ML models from experimentation to production across teams or business units.
- Design and implement integrations using Model Context Protocol to connect AI models with external tools, APIs, and data sources.
- Demonstrated ability to set research and development direction based on business needs.
- Possesses and applies moderate to complex knowledge of particular product or platform to the completion of assignments.
- 3+ years experience interfacing and partnering with vendors.
- 3+ years experience assisting in strategy/roadmap and planning.
- Strong communication skills and ability to communicate at all levels of the organization (technical and business).
- 2+ years experience leading/mentoring more junior staff members.
- Highly self-motivated, directed, ability to work independently and be results-driven.
- 5+ years experience with SharePoint for document management and sharing.
- 5+ years experience with IT ticketing software (Quality Center, ServiceNow, JIRA).
- 3+ years experience in agile/waterfall software delivery methodologies.
- 3+ years experience using Jira, Bitbucket and Confluence agile toolsets or similar.
- 5+ years experience working with small, geographically distributed teams.
- 5+ years experience working both independently and in a team oriented, collaborative environment.
- Ability to be flexible while delivering assignments with understanding that deliverables may change based on business needs.
EDUCATION REQUIREMENTS –
- Bachelor’s degree or foreign equivalent in computer science, engineering or related field or equivalent work experience.
Principal Duties and Responsibilities –
- AI Architecture & Strategy: Design scalable AI/ML architectures and define long-term AI technology strategy aligned with business objectives.
- Model Development: Lead development of machine learning, deep learning, and generative AI models for production environments.
- Technical Leadership: Mentor AI engineers, data scientists, and ML engineers; set engineering standards and best practices.
- Research & Innovation: Evaluate emerging AI technologies and integrate cutting-edge methods into products and platforms.
- Production Deployment: Oversee model deployment, monitoring, optimization, and lifecycle management in cloud or on-prem environments.
- Cross-Functional Collaboration: Work closely with product managers, data engineers, and business stakeholders to translate requirements into AI solutions.
- Responsible AI & Governance: Ensure ethical AI practices, model explainability, fairness, privacy, and regulatory compliance.
- Performance Optimization: Improve model accuracy, efficiency, scalability, and reliability for enterprise-scale systems.
ADDITIONAL CHARACTERISTICS –
- Independently performs assignments to achieve stated objective. Determines and develops approach to solutions.
- Receives technical guidance only on unusual or complex problems or issues.
- May be responsible for entire projects having moderate to complex scope/impact or portions of projects having considerable scope/impact.
- Uses judgment and discretion to determine work priorities, receiving little instruction from others.
LI-GW1
Committed to diversity and inclusion
At Manhattan, it’s about more than just the work. From cultural celebrations to interest groups to volunteer opportunities, your true self is always welcome here. Our team members’ backgrounds, experiences and perspectives add to us as a whole and make us unique.
We are proudly an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a veteran. In the United States, Manhattan Associates participates in the Employment Eligibility Verification Program (E-Verify) operated by the Department of Homeland Security in partnership with the Social Security Administration. Participation in the E-Verify Program allows Manhattan to confirm the employment eligibility of all newly hired employees after the Employment Eligibility Verification Form (Form I-9) has been completed.
AI Engineer Job Roles in Georgia
See all 244+ AI Engineer Jobs in Georgia
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Search AI Engineer Jobs in GeorgiaAI Engineer Jobs in Georgia: Frequently Asked Questions
Which companies sponsor visas for AI engineers in Georgia?
Major H-1B sponsors for AI engineering roles in Georgia include NCR Voyix, Cox Enterprises, Delta Air Lines, Equifax, and UPS, all headquartered in or near Atlanta. Global technology firms like Google, Microsoft, and IBM maintain Georgia offices that also file H-1B petitions for AI engineering positions. Georgia Tech's startup ecosystem has produced additional sponsors, particularly in fintech, supply chain AI, and healthcare informatics.
Which visa types are most common for AI engineer roles in Georgia?
The H-1B is by far the most common visa category for AI engineers in Georgia, as the role qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, data science, or a related field. Candidates with advanced research profiles may also see O-1A petitions. International students completing degrees at Georgia Tech or other Georgia universities often work under OPT or STEM OPT before transitioning to employer-sponsored H-1B status.
Which cities in Georgia have the most AI engineer sponsorship jobs?
Atlanta accounts for the overwhelming majority of AI engineer visa sponsorship activity in Georgia. Specific concentrations appear in Midtown, where Georgia Tech's campus anchors a research and startup corridor, and in Buckhead and Alpharetta, where financial services and enterprise technology firms cluster. Alpharetta in particular has grown as a secondary technology hub, with a number of cybersecurity and data infrastructure companies that hire AI engineers.
How to find ai engineer visa sponsorship jobs in Georgia?
Migrate Mate filters AI engineer job listings specifically by visa sponsorship availability, so you can browse Georgia-based roles without sorting through positions that do not support international candidates. The platform is built for international job seekers, making it straightforward to identify which Atlanta-area employers are actively sponsoring for AI engineering titles like machine learning engineer, MLOps engineer, or applied scientist without contacting companies one by one.
Are there state-specific considerations for AI engineers pursuing sponsorship in Georgia?
Georgia Tech is one of the top producers of AI and machine learning talent in the United States, which means Georgia employers are experienced with international hiring and university OPT pipelines. The state's concentration in logistics, financial services, and healthcare creates consistent demand for AI engineers with domain-specific experience in those verticals. Employers filing H-1B petitions in Georgia must meet Department of Labor prevailing wage requirements for the Atlanta metropolitan area, which are determined by the specific job title and level filed.
What is the prevailing wage for sponsored ai engineer jobs in Georgia?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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