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Generative Ai Developer Jobs in Georgia (NOW HIRING)

GEI Consultants

AI Engineer

Atlanta, GA · On-site

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

GEI Consultants

AI Engineer

Atlanta, GA

$110K - $150K/yr

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

Kaleris

Sr AI Developer

Alpharetta, GA

$53.25 - $70.25/hr

Design and implement generative AI features using LLMs (GPT-4+, Claude, Gemini, etc.) * Build ... Mentor developers, analysts, and solution engineers in multidisciplinary squads * Foster ...

Kaleris

Sr AI Developer

Alpharetta, GA · On-site

$53.25 - $70.25/hr

Design and implement generative AI features using LLMs (GPT-4+, Claude, Gemini, etc.) * Build ... Mentor developers, analysts, and solution engineers in multidisciplinary squads * Foster ...

Virtual Networx

Gen AI/ ML Engineer

Atlanta, GA · Hybrid

Generative AI & LLMs: GPT, LLaMA, Claude, BERT, PEFT/LoRA, Prompt Engineering * Frameworks & Search: LangChain, RAG Pipelines, Vector Databases, Semantic Search * Cloud Platforms: Azure (Cognitive ...

AIG

Generative AI Product Owner

Atlanta, GA

Generative AI Product Owner Be part of something groundbreaking At AIG, we are making long-term ... We will incorporate best-in-class engineering and product management principles and your guidance ...

Carrier

AI & Data Solution Architect

Atlanta, GA · On-site

... Generative AI and Agentic AI, including: * LLM integration with tools, APIs, and knowledge bases (RAG patterns) * Autonomous and semi-autonomous agent workflows * Fine-tuning, prompt engineering, and ...

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How much do generative ai developer jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for generative ai developer in Georgia is $38.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.90 and $46.30 per hour, depending on experience, location, and employer.

What are some common challenges faced by Generative AI Developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What are the key skills and qualifications needed to thrive as a Generative AI Developer, and why are they important?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

Is generative AI a good career?

Generative AI is a growing field with increasing demand for developers skilled in machine learning, deep learning, and neural networks. Careers in this area often require knowledge of programming languages like Python and familiarity with AI frameworks such as TensorFlow or PyTorch, offering opportunities in technology, research, and industry applications.

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

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

What is the salary of a generative AI developer?

The salary of a generative AI developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with expertise in deep learning frameworks and large language models can earn higher compensation, often exceeding $180,000. Many positions also offer benefits such as bonuses, stock options, and flexible schedules.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence development, such as a senior Generative AI Developer or AI research lead, often involving advanced skills in machine learning, deep learning, and large language models. These roles usually require extensive experience, specialized knowledge, and may include responsibilities like designing AI systems, managing teams, or overseeing AI strategy in organizations with competitive compensation packages. Such salaries are rare and generally found in top tech companies or specialized AI firms.

What is a Generative AI Developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.

Which 3 jobs will survive AI?

For a Generative AI Developer, roles that require complex human judgment, creativity, and emotional intelligence are likely to persist, such as AI ethics specialists, creative professionals, and strategic consultants. These jobs involve nuanced decision-making and interpersonal skills that AI cannot fully replicate. Continuous learning and expertise in AI tools and programming languages will also help ensure job security in this field.
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What cities in Georgia are hiring for Generative Ai Developer jobs? Cities in Georgia with the most Generative Ai Developer job openings:
Generative Ai Developer jobs near you
Infographic showing various Generative Ai Developer job openings in Georgia as of June 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $79,540 per year, or $38.2 per hour.

Senior AWS Cloud & Generative AI Engineer

Purple Drive Technologies

Atlanta, GA • On-site

$53.50 - $71.75/hr

Full-time

Posted 5 days ago

Job description

Overview:
Key Responsibilities:
  • Design, develop, and implement Generative AI solutions leveraging Amazon Bedrock and related AWS services.
  • Configure and optimize Amazon Bedrock Agent Orchestration for intelligent workflow and model lifecycle management.
  • Apply Prompt Engineering methodologies for fine-tuning and optimizing AI model outputs.
  • Implement Amazon Bedrock Guardrails to ensure compliance, brand safety, and responsible AI governance.
  • Integrate and manage Amazon Knowledge Bases and Vector Databases to enhance contextual understanding and retrieval-augmented generation (RAG) workflows.
  • Employ MLOps practices to automate model training, deployment, and monitoring within enterprise environments.
  • Build and maintain CI/CD pipelines to support scalable and efficient deployment of AI and cloud-native applications.
  • Utilize AWS services including CloudFormation, CDK, Step Functions, Lambda, EventBridge, DynamoDB, S3, Glue, and Athena to design and orchestrate robust cloud infrastructures.
  • Develop infrastructure as code (IaC) solutions using AWS CDK and CloudFormation, ensuring version control and repeatable deployments.
  • Collaborate with data scientists, solution architects, and DevOps teams to integrate AI capabilities with existing business systems.
  • Create and maintain comprehensive technical documentation, including runbooks, design documents, and troubleshooting guides for deployed solutions.
  • Ensure all solutions meet AWS best practices for security, compliance, scalability, and cost optimization.
Required Skills & Experience:
  • 10+ years of hands-on experience in AWS Cloud Computing within enterprise environments.
  • Proven experience with Amazon Bedrock, including agent orchestration, workflow management, and model fine-tuning.
  • Strong knowledge of Generative AI architectures, LLM integration, and Prompt Engineering techniques.
  • Expertise in AWS Cloud Development Kit (CDK), CloudFormation, and Infrastructure as Code (IaC) principles.
  • Proficiency with AWS services such as S3, Lambda, EventBridge, DynamoDB, Glue, Step Functions, and Athena.
  • Experience implementing MLOps pipelines using AWS-native tools and frameworks.
  • Solid understanding of CI/CD pipeline automation using AWS or third-party tools (e.g., CodePipeline, Jenkins, GitHub Actions).
  • Familiarity with security and compliance standards for AI and cloud environments.
  • Strong problem-solving, analytical, and communication skills, with a proven ability to work collaboratively across technical and non-technical teams.
Preferred Qualifications:
  • AWS Certified Solutions Architect / DevOps Engineer / Machine Learning Specialty certification.
  • Experience deploying Retrieval-Augmented Generation (RAG) systems using AWS Bedrock and vector search technologies.
  • Prior experience integrating LLMs (e.g., Anthropic Claude, Amazon Titan, or other Bedrock models) into enterprise solutions.
  • Working knowledge of Python, TypeScript, or Java for automation and API integration.

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