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Internship Ai Infrastructure Engineer Jobs in Georgia

YO AI Labs

AI/ML Engineer - Remote

Atlanta, GA · Remote

$200 - $350/hr

Remote Job Summary We are seeking an experienced AI/ML Engineer to build and deploy secure, scalable AI solutions for mission-critical initiatives while contributing to proprietary AI infrastructure.

PGTEK

HPC Infrastructure Engineer - Travel role

Atlanta, GA · On-site

$90K - $100K/yr

Infrastructure / High-Performance Computing (HPC) Support Engineer We are seeking an Infrastructure ... Experience supporting High-Performance Computing (HPC), AI, GPU, or clustered compute environments

PGTEK

HPC Infrastructure Engineer - Travel role

Atlanta, GA · On-site

$90K - $100K/yr

Infrastructure / High-Performance Computing (HPC) Support Engineer We are seeking an Infrastructure ... Experience supporting High-Performance Computing (HPC), AI, GPU, or clustered compute environments

4P Consulting Inc.

DevOps Engineer IV 4P/763

Atlanta, GA · On-site

$50.75 - $69.50/hr

... infrastructure, AI platforms, and DevOps automation. The ideal candidate will have expertise in ... Google Cloud Platform (GCP) (preferred), Azure, Infrastructure as Code (IaC), cloud security, CI/CD ...

UKG

Staff AI FinOps Governance Lead

Alpharetta, GA · On-site

... infrastructure economics, and cross-functional program leadership to ensure AI innovation is delivered efficiently and sustainably. You will partner closely with Engineering, Product, Finance ...

UKG

Staff AI FinOps Governance Lead

Atlanta, GA · On-site

... infrastructure economics, and cross-functional program leadership to ensure AI innovation is delivered efficiently and sustainably. You will partner closely with Engineering, Product, Finance ...

MasterCard

Senior AI Platform Engineer (DevOps)

Atlanta, GA · On-site

$125K - $160K/yr

Our mission is to provide scalable, secure, and reliable AI infrastructure that enables teams ... Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty ...

Deloitte

Workplace Engineer III/M365

Atlanta, GA

Cloud Infrastructure Engineer III - Workplace Engineering/M365 AI & Engineering helps organizations build, deploy, and operate integrated solutions across software, data, AI, networks, and hybrid ...

NTT DATA Americas, Inc

AI / ML Engineer

Sandy Springs, GA · On-site

$60 - $70/hr

Business Consultant - AI/ML Engineer Location: Atlanta/Chicago Employment Type: Contract/Permanent ... We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a ...

CYNET SYSTEMS

AI Engineer

Atlanta, GA · On-site

$50 - $55/hr

Engineer prompts and contextual workflows to improve LLM response quality and relevance ... Exposure to Azure cloud services and AI infrastructure. Skills: * Backend Development: Java 17 ...

CYNET SYSTEMS

AI Engineer

Atlanta, GA · On-site

$55 - $60/hr

Exposure to Azure cloud services and AI infrastructure. * Healthcare domain experience. Skills ... Prompt Engineering. * HTML5. * CSS3. Qualification And Education: * Bachelor's or Master's degree ...

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All JobsAi Infrastructure Engineer JobsInternship Ai Infrastructure Engineer JobsInternship Ai Infrastructure Engineer Jobs in Georgia

Internship Ai Infrastructure Engineer information

What does an internship AI infrastructure engineer do?

An Internship AI Infrastructure Engineer assists in designing, developing, and maintaining the foundational systems that support artificial intelligence (AI) applications. They work with cloud platforms, data pipelines, and scalable computing resources to ensure that AI models can be trained and deployed efficiently. Interns may help automate workflows, optimize performance, and collaborate with data scientists and software engineers. The role provides hands-on experience with the tools and frameworks commonly used in AI engineering environments.

What types of projects and responsibilities can an internship AI infrastructure engineer expect to work on?

As an AI Infrastructure Engineer intern, you can expect to be involved in projects that support the development, deployment, and scaling of AI models. Typical responsibilities may include optimizing data pipelines, maintaining and improving cloud or on-premise computing resources, and collaborating closely with data scientists to ensure efficient model training and inference. Interns often get hands-on experience with tools such as Docker, Kubernetes, and various cloud platforms, and work in cross-functional teams to troubleshoot and enhance AI workflows. This role provides a solid foundation in both software engineering and AI operations, preparing you for advanced positions in the field.

What are the key skills and qualifications needed to thrive as an internship AI infrastructure engineer, and why are they important?

To thrive as an Internship AI Infrastructure Engineer, you need a solid understanding of computer science fundamentals, programming (especially in Python or C++), and basic knowledge of machine learning frameworks, often supported by ongoing studies in a relevant field. Familiarity with cloud platforms (like AWS, GCP, or Azure), version control systems (such as Git), and containerization tools (Docker, Kubernetes) is typically expected. Strong problem-solving abilities, curiosity, teamwork, and effective communication help interns stand out and integrate quickly into engineering teams. These skills are crucial for supporting scalable AI solutions, collaborating on complex projects, and contributing meaningfully in a fast-evolving technical environment.

What is the difference between Internship Ai Infrastructure Engineer vs Data Engineer?

AspectInternship Ai Infrastructure EngineerData Engineer
Required CredentialsEnrolled in or recent graduate of Computer Science, Engineering, or related fields; some knowledge of AI and infrastructure toolsBachelor's or higher in Computer Science, Data Science, or related; experience with databases and data pipelines
Work EnvironmentInternship setting, collaborative teams, learning-focusedFull-time, technical teams managing data systems and pipelines
Employer & Industry UsageTech companies, AI startups, research labsTech firms, finance, healthcare, and other data-driven industries

The Internship Ai Infrastructure Engineer role focuses on supporting AI infrastructure projects during an internship, emphasizing learning and assisting with AI systems setup. In contrast, Data Engineers build and maintain data pipelines and infrastructure for data analysis. While both roles require knowledge of technical tools, the internship role is more entry-level and learning-oriented, whereas Data Engineers are more experienced and responsible for ongoing data management.

What are the most commonly searched types of Ai Infrastructure Engineer jobs in Georgia?

The most popular types of Ai Infrastructure Engineer jobs in Georgia are:

What are popular job titles related to Internship Ai Infrastructure Engineer jobs in Georgia?

For Internship Ai Infrastructure Engineer jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Internship Ai Infrastructure Engineer jobs in Georgia look for?

The top searched job categories for Internship Ai Infrastructure Engineer jobs in Georgia are:

What cities in Georgia are hiring for Internship Ai Infrastructure Engineer jobs?

Cities in Georgia with the most Internship Ai Infrastructure Engineer job openings:

Internship Ai Infrastructure Engineer jobs near you
Infographic showing various Internship Ai Infrastructure Engineer job openings in Georgia as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 72% Physical, 3% Hybrid, and 25% Remote job distribution.

Developer & Infrastructure Expert - Remote

YO AI Labs

Atlanta, GA • Remote

$30 - $80/hr

Full-time

Posted 9 days ago

Job description

Developer & Infrastructure Expert

Role Type: Contractor
Location: Remote

Job Overview

We are seeking experienced Developer & Infrastructure Experts to evaluate AI-powered workflows across software development, cloud infrastructure, DevOps, SRE, and platform engineering. You will test AI-generated commands, configurations, and workflows and provide practical feedback based on real-world engineering standards.

No prior AI experience is required—your technical expertise and infrastructure knowledge are what matter most.

Key Responsibilities
  • Test and validate AI-assisted workflows across DevOps, cloud, infrastructure, and platform engineering.
  • Evaluate AI-generated commands, configurations, scripts, and deployment workflows for accuracy and reliability.
  • Work with AWS, Azure, GCP, Kubernetes, Docker, Terraform, and CI/CD environments.
  • Review workflows involving GitHub, GitLab, Azure DevOps, and JIRA.
  • Assess AI agents and workplace connectors across tools such as Slack, Google Drive, and Microsoft 365.
  • Identify technical errors, security or reliability concerns, and workflow gaps.
  • Document findings and provide clear, actionable feedback.
  • Recommend improvements based on real-world engineering practices and industry standards.
  • Collaborate remotely with project stakeholders through written evaluations and virtual discussions.
Required Skills
  • Azure DevOps
  • Cloud Infrastructure
  • Site Reliability Engineering (SRE)
  • Platform Engineering
  • AWS / Azure / GCP
  • Kubernetes / Docker
  • Terraform
  • CI/CD
  • GitHub / GitLab / JIRA
  • Observability
  • ChatGPT Work
  • Claude Code
  • Claude Cowork
  • AI Agents
  • Workplace Connectors
Preferred Qualifications
  • Professional experience in software engineering, DevOps, SRE, cloud, platform, or infrastructure engineering.
  • Hands-on experience with major cloud platforms, Kubernetes, Docker, Terraform, CI/CD, and observability tools.
  • Experience with developer workflow and project management platforms such as GitHub, GitLab, Azure DevOps, and JIRA.
  • Experience using AI agents such as ChatGPT, Claude Code, Claude Cowork, or Codex in development or infrastructure workflows.
  • Strong ability to evaluate technical processes and provide actionable feedback.
  • Excellent written and verbal communication skills.
  • Experience with workplace connectors, automation, or AI-powered infrastructure workflows is a plus.