1

Intern Ai Agent Developer Jobs in Georgia (NOW HIRING)

FSE Sr.AI Engineer

Atlanta, GA · On-site

$117K - $155K/yr

... and agent-ready task breakdowns before writing any code. * Design and build full stack web ... Build and integrate AI-powered features -- leveraging LLMs, AI agents, prompt engineering, and the ...

As our Senior Data Engineer, you will report to the Senior Engineering Manager for the Fullstory ... You have helped shape the AI agent platform's technical direction, from eval frameworks to MCP ...

Senior AI Engineer (Remote)

Atlanta, GA · On-site +1

$99K - $136K/yr

You will build the core orchestration layers for multi-agent workflows, tool integration, and ... Works with Product Team to ensure user stories that are developer-ready, easy to understand, and ...

Job Summary : Bricklayer AI is a pioneering company offering a multi-agent LLM-based AI solution for security. The Platform Engineering Leader will drive the strategic vision and execution of the ...

Senior AI Engineer

Atlanta, GA · On-site

$140 - $200/hr

Develop key AI architecture patterns (RAG, text-to-sql, multi-agent, etc)Create end-to-end production grade AI agents and integrate them into applicationsApply prompt engineering and context ...

Senior AI Solutions Engineer

Marietta, GA · On-site

$128K - $216K/yr

Job Title Senior AI Solutions Engineer About the role As a Senior AI Solutions Engineer, you will ... Design multi-step agent architectures: tool use, retrieval (RAG), memory, orchestration across ...

Showing results 41-60

Intern Ai Agent Developer information

What does an Intern AI Agent Developer do?

An Intern AI Agent Developer assists in designing, developing, and testing artificial intelligence agents, which are software programs capable of performing tasks that typically require human intelligence. Their responsibilities may include writing code, training machine learning models, analyzing data, and supporting senior developers in research or project work. Interns in this role gain hands-on experience with AI frameworks and tools while learning best practices in software engineering and artificial intelligence development.

What types of projects and tasks can an Intern AI Agent Developer expect to work on during their internship?

As an Intern AI Agent Developer, you will typically collaborate with experienced engineers and data scientists to design, develop, and test components of AI-driven systems. Your daily tasks may include writing and debugging code, assisting in training machine learning models, and running experiments to evaluate agent performance. Interns often contribute to documentation, participate in code reviews, and may even help implement features under supervision. This role provides a hands-on learning environment where you can develop both technical and teamwork skills, while gaining exposure to the latest AI development tools and practices.

What is the difference between Intern Ai Agent Developer vs Intern Machine Learning Engineer?

AspectIntern Ai Agent DeveloperIntern Machine Learning Engineer
Required CredentialsRelevant coursework, basic programming skills, familiarity with AI toolsRelevant coursework, programming skills, understanding of ML algorithms
Work EnvironmentTech companies, AI startups, research labsTech companies, research institutions, AI startups
Employer & Industry UsageAI development teams, chatbot and virtual assistant projectsData science teams, predictive modeling projects

Intern Ai Agent Developers focus on building and improving AI agents like chatbots and virtual assistants, often requiring knowledge of AI frameworks. Intern Machine Learning Engineers work on developing ML models for various applications, emphasizing data handling and algorithm implementation. Both roles are common in tech and AI industries, but they differ in specific focus areas and skill sets.

What are the key skills and qualifications needed to thrive as an Intern AI Agent Developer?

To thrive as an Intern AI Agent Developer, you need a solid understanding of programming languages like Python, basic knowledge of machine learning concepts, and enrollment in or completion of a relevant degree such as computer science. Familiarity with tools and frameworks such as TensorFlow, PyTorch, Git, and cloud platforms is typically expected. Curiosity, strong problem-solving skills, and the ability to collaborate within a team help you stand out. These skills are crucial for successfully contributing to AI projects, learning quickly in a dynamic field, and effectively supporting development teams.
What are the most commonly searched types of Ai Agent Developer jobs in Georgia? The most popular types of Ai Agent Developer jobs in Georgia are:
What job categories do people searching Intern Ai Agent Developer jobs in Georgia look for? The top searched job categories for Intern Ai Agent Developer jobs in Georgia are:
What cities in Georgia are hiring for Intern Ai Agent Developer jobs? Cities in Georgia with the most Intern Ai Agent Developer job openings:
Infographic showing various Intern Ai Agent Developer job openings in Georgia as of August 2026, with employment types broken down into 75% Full Time, 20% Part Time, 1% Temporary, and 4% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution.

Manager, Forward-Deployed AI Engineer - AI Mobilization & Transformation

MasterCard

Atlanta, GA

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago


Job description

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build asustainableeconomy where everyone can prosper. We support a wide range of digital payments choices, making transactionssecure, 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

Manager, Forward-Deployed AI Engineer - AI Mobilization & TransformationOverview
The Manager, Forward-Deployed AI Engineer serves as Mastercard's embedded AI transformation leader, partnering directly with business units to identify high-value opportunities, develop production-grade AI solutions, and mobilize teams to adopt new ways of working.
Reporting to the Director, Forward-Deployed AI Engineer - AI Mobilization & Transformation, this role combines deep technical expertise with change leadership. Rather than building solutions in isolation, you will work alongside business teams to solve real problems, demonstrate the art of the possible, and develop internal capability through hands-on engagement.
Success is measured not only by the solutions delivered, but by the number of leaders, engineers, analysts, and teams equipped to independently leverage AI, agents, and multi-agent systems in their daily work.
The Role
Mobilizing AI Adoption Through Bespoke Engagements
Embed within business units to identify strategic workflow, productivity, and decision-making opportunities where AI can create measurable value.
Lead AI Transformation Engagements that combine discovery, solution design, implementation, and capability building.
Build high-impact use cases that serve as showcase examples for broader organizational adoption.
Translate business challenges into practical applications of AI, agents, and multi-agent orchestration.
Create reusable playbooks, patterns, and training assets that accelerate adoption across the enterprise.
Partner with business leaders to demonstrate measurable outcomes and establish local AI champions.
Support the identification and delivery of high-value AI opportunities across business functions.
Contribute reusable assets and implementation patterns that accelerate future engagements.
Building While Teaching
Design and deploy production-ready AI assistants, agents, and orchestration frameworks that solve real business problems.
Use each engagement as a live learning environment where business and technical teams learn modern AI practices through delivery.
Coach engineers, analysts, product managers, knowledge workers, and operational teams on AI-first ways of working.
Establish a "train-the-trainer" model that enables local teams to continue scaling capabilities after engagements conclude.
Facilitate hands-on workshops focused on prompt engineering, agent design, workflow automation, Copilot practices, and AI-assisted development.
Develop practitioners capable of independently applying AI tools and techniques within their teams.
Promote knowledge sharing and adoption of established AI best practices.
Advancing Agentic Transformation
Architect and implement solutions leveraging Copilot Studio, Azure AI, agent frameworks, orchestration systems, and enterprise platforms.
Develop multi-agent solutions that automate complex business processes and decision flows.
Introduce modern engineering practices including AI-assisted software development, evaluation frameworks, observability, and governance.
Establish proven reference architectures and patterns that can be replicated across business units.
Help business teams evolve from experimentation to operationalized AI solutions.
Apply established AI patterns and frameworks to accelerate solution delivery and adoption.
Evaluate emerging AI capabilities and assist in translating them into practical business applications.
Capturing and Scaling Organizational Learning
Document emerging patterns, successful use cases, implementation approaches, and lessons learned.
Build an enterprise library of AI-enabled workflows, agents, and transformation stories.
Identify adoption barriers and design interventions that accelerate organizational readiness.
Contribute to enterprise readiness metrics by measuring adoption, productivity gains, capability growth, and business impact.
Create a feedback loop between field engagements, engineering teams, and organizational readiness programs.
Capture reusable assets, implementation approaches, and best practices from engagements.
Share lessons learned to improve future AI transformation efforts across the organization.
All About You
Extensive software engineering experience with a track record of building and deploying production-grade systems.
Deep experience with AI technologies including LLMs, agent frameworks, RAG architectures, orchestration patterns, and AI application development.
Experience building and deploying enterprise AI solutions that deliver measurable business outcomes.
Strong facilitation and coaching abilities, with experience educating technical and non-technical audiences.
Comfortable working directly with business stakeholders to identify opportunities and redesign workflows.
Proven ability to influence organizational change through hands-on partnership and delivery.
Experience mentoring and developing technical talent through real-world project engagements.
Strong understanding of responsible AI, governance, risk management, and production monitoring practices.
Ability to translate complex technical concepts into practical business value and adoption strategies.
Experience supporting cross-functional initiatives that combine AI adoption, workflow transformation, and capability development.
Demonstrated ability to build relationships and influence stakeholders across technical and business teams.
Experience documenting and sharing repeatable patterns, practices, or implementation approaches.
Strong communication skills with the ability to explain AI concepts to both technical and non-technical audiences.
Experience driving adoption of new technologies through hands-on engagement and coaching.
Experience with Copilot Studio, Azure AI, GitHub Copilot, Claude Code, or equivalent platforms preferred.
Financial services, payments, or enterprise transformation experience preferred.
Passion for developing others and creating sustainable capability within organizations.
Success in This Role
Success is not measured by the number of agents you build. Success is measured by the number of teams that can build without you.
You leave behind:
New organizational capability.
Repeatable AI patterns.
Trained champions and practitioners.
Demonstrated business value.
Sustainable adoption of AI-first ways of working.
Increased confidence and proficiency in applying AI across day-to-day work.
Reusable assets and implementation practices that accelerate future adoption.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.

Pay Ranges

Purchase, New York: $161,000 - $266,000 USDArlington, Virginia: $161,000 - $266,000 USDAtlanta, Georgia: $140,000 - $231,000 USD