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Intern Ai Agent Developer Jobs in Decatur, GA (NOW HIRING)

KPMG

Manager, SAP AI & Agent Governance

Atlanta, GA · On-site

KPMG is currently seeking a Manager, SAP AI & Agent Governance to join our Advisory Technology ... Bachelor'sdegree in business, information systems, engineering, technology, or relatedfield ...

KPMG

Manager, SAP AI & Agent Governance

Atlanta, GA · On-site

KPMG is currently seeking a Manager, SAP AI & Agent Governance to join our Advisory Technology ... Bachelor'sdegree in business, information systems, engineering, technology, or relatedfield ...

Insight Global

Back End Developer

Atlanta, GA · On-site

As a Back-end Developer - AI Agent Foundry - Automation Team you will develop and deploy microservices, REST APIs to support the Agent Foundry Data Platform. At Evergreen, we value creativity ...

Digital Insight

Principal AI Engineer

Atlanta, GA · Remote

The Principal AI Engineer is responsible for driving AI adoption and innovation across Corporate ... AI-assisted agent experiences * Knowledge retrieval systems * Intelligent intake and triage ...

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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 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 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.

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Intern Ai Agent Developer jobs near you

Google Cloud AI Solutions Architect, Gemini Enterprise

Atlanta, GA

The Data Sherpas
See more jobs at The Data Sherpasexternal

$61 - $83.75/hr

Full-time

Re-posted 26 days ago

Job description

Google Cloud AI Solutions Architect, Gemini Enterprise


Overview

We are seeking a hands-on Google Cloud AI Solutions Architect to design, build, configure, and implement Gemini Enterprise and agentic AI solutions for end clients. This is a client-facing technical delivery role focused on applied AI/ML implementation, not sales.

The right candidate will have strong Google Cloud experience, hands-on Gemini Enterprise or Google Cloud generative AI implementation experience, and the ability to translate client workflows into secure, scalable, production-ready AI solutions. This person should be comfortable moving between architecture, coding, prototyping, configuration, integration, and client-facing technical delivery.


Responsibilities

  • Design, build, configure, and implement Gemini Enterprise solutions for end clients.
  • Develop AI agent workflows that support business use cases, internal processes, enterprise automation, and operational workflows.
  • Build prototypes and proofs of concept that can be iterated into production-ready solutions.
  • Design and implement applied AI/ML solutions using Gemini Enterprise, Vertex AI, and related Google Cloud AI services.
  • Build and deploy LLM-powered applications, AI agents, retrieval-augmented generation workflows, and enterprise AI integrations.
  • Evaluate model options, agent patterns, grounding strategies, retrieval approaches, and integration paths based on client use cases.
  • Configure and deploy Gemini Enterprise agents, integrations, and related Google Cloud AI services.
  • Integrate AI agents with enterprise systems, data sources, APIs, and business applications.
  • Lead technical discovery with clients and translate requirements into solution architecture and implementation plans.
  • Develop scripts, connectors, workflows, or lightweight applications needed to support AI agent implementation.
  • Support model evaluation, prompt optimization, testing, validation, troubleshooting, and production readiness.
  • Apply best practices for cloud security, IAM, data governance, responsible AI, monitoring, and enterprise deployment.
  • Communicate technical recommendations clearly to client engineering, data, security, cloud, and business stakeholders.


Qualifications

  • Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Machine Learning, or a related field; equivalent practical experience will also be considered.
  • 5+ years of experience in cloud architecture, AI/ML solution architecture, technical consulting, solution architecture, software engineering, or hands-on client-facing technical delivery.
  • 3+ years of experience working with Google Cloud Platform.
  • Google Cloud Professional Cloud Architect or Google Cloud Professional Machine Learning Engineer certification.
  • Hands-on experience implementing Gemini Enterprise or Google Cloud generative AI solutions.
  • Hands-on experience designing or implementing AI/ML solutions using Google Cloud AI services, including Vertex AI, Gemini, Gemini Enterprise, Agent Builder, Agent Development Kit, or related tools.
  • Experience building, configuring, deploying, or integrating AI agents, generative AI applications, LLM-powered applications, or enterprise AI workflows.
  • Experience building agentic AI workflows using Google Cloud Agent Development Kit, Vertex AI Agent Engine, Agent Builder, or related agent development tools.
  • Experience with core agentic AI implementation patterns such as retrieval-augmented generation, prompt engineering, tool use/function calling, API integrations, enterprise system integration, and/or multi-agent workflows.
  • Experience with LLM application development, embeddings, model evaluation, prompt optimization, and production AI/ML implementation patterns.
  • Strong understanding of Google Cloud AI and data services, such as Vertex AI, Gemini, Gemini Enterprise, BigQuery, BigQuery ML, Cloud Functions, Cloud Run, APIs, IAM, and related services.
  • Ability to code, script, prototype, and troubleshoot technical solutions in client environments.
  • Experience working directly with enterprise clients or internal business stakeholders to gather requirements and implement technical solutions.
  • Strong understanding of cloud security, IAM, data governance, responsible AI, and enterprise deployment best practices.
  • Excellent communication skills with the ability to explain complex technical concepts clearly.
  • Must be a U.S. Citizen.


Preferred Skills

  • Google Cloud Generative AI Leader certification.
  • Experience as a Forward Deployed Engineer, Solutions Architect, AI Architect, ML Engineer, Customer Engineer, Technical Consultant, or hands-on implementation architect.
  • Experience with Python, JavaScript, TypeScript, or similar programming languages.
  • Experience with data integration, workflow automation, enterprise applications, embeddings, vector search, semantic search, model grounding, enterprise search, or retrieval-augmented generation pipelines.
  • Experience in consulting, systems integration, professional services, or client-facing technical delivery.
  • Familiarity with infrastructure as code, CI/CD, containers, serverless architecture, and cloud-native application deployment.


Additional Information

This position is open to direct candidates only. We are not working with third-party agencies, subcontractors, or C2C arrangements for this role.


Candidates must be U.S. Citizens.

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