Lead Platform Engineer Visa Sponsorship Jobs in Georgia
Lead platform engineer roles in Georgia draw sponsorship activity from Atlanta's dense concentration of fintech, media, and enterprise technology employers, including Cox Enterprises, NCR Atleos, and Global Payments. Metro Atlanta dominates hiring volume, though Alpharetta and Midtown corridors also host significant engineering teams. Candidates from abroad have several visa pathways available for these senior infrastructure and distributed-systems roles.
Find Lead Platform Engineer JobsOverview
Showing 5 of 25+ Lead Platform Engineer Jobs in Georgia with Visa Sponsorship
See all Lead Platform Engineer Jobs in Georgia with Visa Sponsorship
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Lead Platform Engineer Jobs in Georgia with Visa Sponsorship.
Get Access To All JobsOur Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart, and accessible. Our technology and innovation, partnerships, and networks combine to deliver a unique set of products and services that help people, businesses, and governments realize their greatest potential.
Title and Summary
Lead AI Platform Engineer
Who is Mastercard?
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we are helping build a sustainable economy where everyone can prosper. We support digital payment choices that make transactions secure, simple, smart, and accessible. Our technology, innovation, partnerships, and networks deliver products and services that help people, businesses, and governments realize their greatest potential.
Overview
The AI Platform Engineering team builds, operates, and evolves Mastercard's enterprise AI platforms. Our mission is to provide scalable, secure, and reliable AI infrastructure that enables teams across Mastercard to accelerate the development and deployment of AI-powered solutions.
As a Lead AI Engineer, you will provide technical leadership in designing, implementing, and operating the foundational platforms supporting AI and machine learning workloads across the enterprise. Working at the intersection of platform engineering, cloud infrastructure, MLOps, and AI operations, you will deliver capabilities that enable teams to safely develop, deploy, observe, and scale AI solutions across public and private cloud environments.
You will help shape the platforms, tooling, operational practices, and infrastructure supporting the next generation of AI capabilities at Mastercard. You will address complex challenges involving scalability, reliability, observability, governance, automation, and customer enablement while influencing stakeholders and contributing to Mastercard's long-term AI platform direction.
About the Role
As a Lead AI Engineer, AI Platform Engineering, you will serve as a developing subject matter expert responsible for advancing the architecture, engineering, automation, and operational excellence of Mastercard's AI platforms. You will lead the technical design and delivery of complex capabilities, improve existing products and processes, and influence decisions across engineering, infrastructure, security, architecture, and governance teams.
The ideal candidate combines advanced software engineering and cloud platform expertise with experience supporting production AI and machine learning systems. You are passionate about technical leadership, automation, reliability, and building platforms that empower others to innovate. You are comfortable operating through influence, reviewing technical work, mentoring engineers, and translating complex requirements into scalable solutions.
Responsibilities
- Lead the design, development, and operation of enterprise platforms supporting machine learning, generative AI, agentic AI, and advanced analytics workloads.
- Translate business, engineering, and operational requirements into scalable platform solutions and implementation approaches.
- Design and maintain advanced AI and machine learning systems that meet enterprise requirements for security, reliability, availability, scalability, and performance.
- Own technical delivery across public and private cloud environments, identifying dependencies, resolving complex challenges, and influencing cross-functional decisions.
- Build and optimize services and workflows that simplify onboarding, development, deployment, operations, and lifecycle management for AI solutions.
- Develop infrastructure, tooling, and services supporting model training, evaluation, fine-tuning, deployment, inference, monitoring, and governance.
- Lead the implementation of repeatable, scalable, and secure MLOps capabilities and AI development workflows.
- Build and optimize data ingestion, preprocessing, and feature engineering workflows supporting model training and inference.
- Design observability capabilities including telemetry, performance monitoring, logging, alerting, operational analytics, model monitoring, and drift detection.
- Ensure the operational stability and scalability of AI platforms, driving improvements to reliability, resilience, efficiency, security, and customer experience.
- Lead troubleshooting, root cause analysis, and incident response for complex platform issues and translate lessons learned into sustainable improvements.
- Influence platform architecture through design discussions, reviews, prototypes, tradeoff analysis, and technical recommendations.
- Partner with engineering and product teams to understand requirements, guide solution design, enable adoption, and accelerate delivery of AI-powered products.
- Collaborate with infrastructure, security, architecture, risk, and governance teams to align capabilities with enterprise standards, controls, ethical guidelines, and regulatory requirements.
- Evaluate emerging AI technologies and industry trends and recommend improvements to Mastercard's AI ecosystem and roadmap.
- Drive engineering best practices across Infrastructure as Code, CI/CD, automated testing, secure development, documentation, and operational excellence.
- Guide and mentor engineers through design guidance, technical reviews, problem-solving support, and knowledge sharing.
All About You
Required Qualifications
- Experience designing, building, and operating cloud-native platforms or large-scale distributed systems in enterprise environments.
- Strong experience delivering solutions across public and private cloud environments.
- Experience deploying and managing containerized workloads using Kubernetes or OpenShift.
- Advanced software engineering and automation experience using Python.
- Experience leading the technical design and delivery of complex initiatives involving multiple teams or stakeholders.
- Experience implementing CI/CD pipelines, Infrastructure as Code, automated testing, and modern DevOps practices.
- Experience designing or supporting production AI, machine learning, data platforms, or distributed systems.
- Strong understanding of MLOps, model lifecycle management, production inference, and AI system operations.
- Experience implementing telemetry, monitoring, logging, alerting, and operational analytics.
- Ability to diagnose complex issues, lead root cause analysis, and implement sustainable corrective actions.
- Ability to assess architectural options, explain technical tradeoffs, and influence cross-functional decisions.
- Ability to communicate effectively with technical and non-technical stakeholders.
- Experience guiding, mentoring, or reviewing the work of other engineers.
Preferred Qualifications
- Experience with enterprise generative AI platforms and large language model workloads.
- Experience with model evaluation, fine-tuning, guardrails, responsible AI controls, and model governance.
- Experience with model observability, drift detection, telemetry, and operational analytics.
- Experience with AI serving infrastructure, inference platforms, or AI gateways.
- Experience supporting GPU-based workloads and accelerated computing environments.
- Experience with OpenShift, Kubernetes, Docker, Helm, GitOps, and Infrastructure as Code.
- Experience with enterprise platform engineering, developer enablement, and self-service capabilities.
- Familiarity with vector databases, retrieval-augmented generation, AI gateways, agentic systems, and model routing.
- Experience operating in regulated environments requiring strong security, governance, risk management, resiliency, and compliance controls.
Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard’s security policies and practices;
- Ensure the confidentiality and integrity of the information being accessed;
- Report any suspected information security violation or breach, and
- Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.
THIS POSTING RELECTS ONE OR MORE CURRENT VACANCIES ON OUR TEAM, AND MASTERCARD INTENDS TO FILL THIS POSITION BY 01/26/2027. If the fill date has passed, Mastercard intends to fill this position as soon as possible.
Pay Ranges
New York City, New York: $168,000 - $277,000 USD
Arlington, Virginia: $161,000 - $266,000 USD
Atlanta, Georgia: $140,000 - $231,000 USD
Austin, Texas: $140,000 - $231,000 USD
Boston, Massachusetts: $161,000 - $266,000 USD
O'Fallon, Missouri: $140,000 - $231,000 USD
Purchase, New York: $161,000 - $266,000 USD
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart, and accessible. Our technology and innovation, partnerships, and networks combine to deliver a unique set of products and services that help people, businesses, and governments realize their greatest potential.
Title and Summary
Lead AI Platform Engineer
Who is Mastercard?
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we are helping build a sustainable economy where everyone can prosper. We support digital payment choices that make transactions secure, simple, smart, and accessible. Our technology, innovation, partnerships, and networks deliver products and services that help people, businesses, and governments realize their greatest potential.
Overview
The AI Platform Engineering team builds, operates, and evolves Mastercard's enterprise AI platforms. Our mission is to provide scalable, secure, and reliable AI infrastructure that enables teams across Mastercard to accelerate the development and deployment of AI-powered solutions.
As a Lead AI Engineer, you will provide technical leadership in designing, implementing, and operating the foundational platforms supporting AI and machine learning workloads across the enterprise. Working at the intersection of platform engineering, cloud infrastructure, MLOps, and AI operations, you will deliver capabilities that enable teams to safely develop, deploy, observe, and scale AI solutions across public and private cloud environments.
You will help shape the platforms, tooling, operational practices, and infrastructure supporting the next generation of AI capabilities at Mastercard. You will address complex challenges involving scalability, reliability, observability, governance, automation, and customer enablement while influencing stakeholders and contributing to Mastercard's long-term AI platform direction.
About the Role
As a Lead AI Engineer, AI Platform Engineering, you will serve as a developing subject matter expert responsible for advancing the architecture, engineering, automation, and operational excellence of Mastercard's AI platforms. You will lead the technical design and delivery of complex capabilities, improve existing products and processes, and influence decisions across engineering, infrastructure, security, architecture, and governance teams.
The ideal candidate combines advanced software engineering and cloud platform expertise with experience supporting production AI and machine learning systems. You are passionate about technical leadership, automation, reliability, and building platforms that empower others to innovate. You are comfortable operating through influence, reviewing technical work, mentoring engineers, and translating complex requirements into scalable solutions.
Responsibilities
- Lead the design, development, and operation of enterprise platforms supporting machine learning, generative AI, agentic AI, and advanced analytics workloads.
- Translate business, engineering, and operational requirements into scalable platform solutions and implementation approaches.
- Design and maintain advanced AI and machine learning systems that meet enterprise requirements for security, reliability, availability, scalability, and performance.
- Own technical delivery across public and private cloud environments, identifying dependencies, resolving complex challenges, and influencing cross-functional decisions.
- Build and optimize services and workflows that simplify onboarding, development, deployment, operations, and lifecycle management for AI solutions.
- Develop infrastructure, tooling, and services supporting model training, evaluation, fine-tuning, deployment, inference, monitoring, and governance.
- Lead the implementation of repeatable, scalable, and secure MLOps capabilities and AI development workflows.
- Build and optimize data ingestion, preprocessing, and feature engineering workflows supporting model training and inference.
- Design observability capabilities including telemetry, performance monitoring, logging, alerting, operational analytics, model monitoring, and drift detection.
- Ensure the operational stability and scalability of AI platforms, driving improvements to reliability, resilience, efficiency, security, and customer experience.
- Lead troubleshooting, root cause analysis, and incident response for complex platform issues and translate lessons learned into sustainable improvements.
- Influence platform architecture through design discussions, reviews, prototypes, tradeoff analysis, and technical recommendations.
- Partner with engineering and product teams to understand requirements, guide solution design, enable adoption, and accelerate delivery of AI-powered products.
- Collaborate with infrastructure, security, architecture, risk, and governance teams to align capabilities with enterprise standards, controls, ethical guidelines, and regulatory requirements.
- Evaluate emerging AI technologies and industry trends and recommend improvements to Mastercard's AI ecosystem and roadmap.
- Drive engineering best practices across Infrastructure as Code, CI/CD, automated testing, secure development, documentation, and operational excellence.
- Guide and mentor engineers through design guidance, technical reviews, problem-solving support, and knowledge sharing.
All About You
Required Qualifications
- Experience designing, building, and operating cloud-native platforms or large-scale distributed systems in enterprise environments.
- Strong experience delivering solutions across public and private cloud environments.
- Experience deploying and managing containerized workloads using Kubernetes or OpenShift.
- Advanced software engineering and automation experience using Python.
- Experience leading the technical design and delivery of complex initiatives involving multiple teams or stakeholders.
- Experience implementing CI/CD pipelines, Infrastructure as Code, automated testing, and modern DevOps practices.
- Experience designing or supporting production AI, machine learning, data platforms, or distributed systems.
- Strong understanding of MLOps, model lifecycle management, production inference, and AI system operations.
- Experience implementing telemetry, monitoring, logging, alerting, and operational analytics.
- Ability to diagnose complex issues, lead root cause analysis, and implement sustainable corrective actions.
- Ability to assess architectural options, explain technical tradeoffs, and influence cross-functional decisions.
- Ability to communicate effectively with technical and non-technical stakeholders.
- Experience guiding, mentoring, or reviewing the work of other engineers.
Preferred Qualifications
- Experience with enterprise generative AI platforms and large language model workloads.
- Experience with model evaluation, fine-tuning, guardrails, responsible AI controls, and model governance.
- Experience with model observability, drift detection, telemetry, and operational analytics.
- Experience with AI serving infrastructure, inference platforms, or AI gateways.
- Experience supporting GPU-based workloads and accelerated computing environments.
- Experience with OpenShift, Kubernetes, Docker, Helm, GitOps, and Infrastructure as Code.
- Experience with enterprise platform engineering, developer enablement, and self-service capabilities.
- Familiarity with vector databases, retrieval-augmented generation, AI gateways, agentic systems, and model routing.
- Experience operating in regulated environments requiring strong security, governance, risk management, resiliency, and compliance controls.
Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard’s security policies and practices;
- Ensure the confidentiality and integrity of the information being accessed;
- Report any suspected information security violation or breach, and
- Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.
THIS POSTING RELECTS ONE OR MORE CURRENT VACANCIES ON OUR TEAM, AND MASTERCARD INTENDS TO FILL THIS POSITION BY 01/26/2027. If the fill date has passed, Mastercard intends to fill this position as soon as possible.
Pay Ranges
New York City, New York: $168,000 - $277,000 USD
Arlington, Virginia: $161,000 - $266,000 USD
Atlanta, Georgia: $140,000 - $231,000 USD
Austin, Texas: $140,000 - $231,000 USD
Boston, Massachusetts: $161,000 - $266,000 USD
O'Fallon, Missouri: $140,000 - $231,000 USD
Purchase, New York: $161,000 - $266,000 USD
Lead Platform Engineer Job Roles in Georgia
See all Lead Platform Engineer Jobs in Georgia
Sign up for free to filter by visa type, set job alerts, and find employers with verified sponsorship history.
Search Lead Platform Engineer Jobs in GeorgiaLead Platform Engineer Jobs in Georgia: Frequently Asked Questions
Which companies in Georgia sponsor visas for lead platform engineers?
Atlanta-headquartered employers including Cox Enterprises, NCR Atleos, Global Payments, Equifax, and Delta Air Lines have active engineering organizations that file Labor Condition Applications for senior platform roles. Midtown Atlanta's technology corridor and the Alpharetta fintech hub also host divisions of large consulting firms and cloud-services companies that sponsor H-1B visa and other work visas for experienced platform engineers.
What visa types realistically apply to lead platform engineer roles in Georgia?
Lead platform engineer is a specialty occupation requiring a directly related bachelor's degree, so the H-1B, E-3 visa (Australian nationals), H-1B1 visa (Chilean and Singaporean nationals), and TN visa (Canadian and Mexican engineers with a qualifying engineering degree) all apply. For longer-term stays, EB-2 or EB-3 employment-based green cards are common pathways. F-1 OPT and STEM OPT can bridge candidates early in their careers before employer-sponsored status is secured.
Which cities in Georgia have the most lead platform engineer sponsorship jobs?
Metro Atlanta accounts for the overwhelming majority of lead platform engineer sponsorship activity in Georgia. Midtown and Buckhead concentrate the largest employer campuses, while Alpharetta hosts a dense cluster of fintech and SaaS companies. Dunwoody and Sandy Springs have growing technology office parks. Outside metro Atlanta, meaningful engineering hiring is limited, so candidates targeting sponsored roles should focus their search on the Atlanta metropolitan area.
How to find lead platform engineer visa sponsorship jobs in Georgia?
Migrate Mate lists Georgia employers with verified sponsorship histories for platform engineering roles, letting you search specifically by role type and location rather than sifting through generalist postings. Because lead platform engineer is a senior, specialized position, filtering to employers with active H-1B or LCA filing records for engineering roles in Atlanta and surrounding areas narrows your search to companies with demonstrated sponsorship intent, saving significant time.
Are there any Georgia-specific factors that affect visa sponsorship for lead platform engineers?
Georgia's large technology ecosystem, anchored by Georgia Tech graduates and the Atlanta metro's fintech and media industries, means many established employers are experienced with the H-1B and LCA process for senior engineering hires. The state has no specific immigration rules, but employers in regulated industries such as financial services and healthcare IT may have additional internal compliance steps. Georgia Tech's research partnerships also create pathways through J-1 visa exchange programs for some platform-engineering research roles.
What is the prevailing wage for sponsored lead platform 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.