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Generative Ai Director Jobs in Georgia (NOW HIRING)

Florence Healthcare - US

Director of AI

Atlanta, GA · On-site

The Director of AI leads the design, development, and delivery of AI-powered capabilities across ... Guide engineers on best practices for Generative AI, Agentic AI, Retrieval-Augmented Generation ...

Florence Healthcare

Director of AI

Atlanta, GA · On-site

Director of AI Atlanta, GA Florence software advances cures by helping the world's most important ... Guide engineers on best practices for Generative AI, Agentic AI, Retrieval-Augmented Generation ...

New

Florence Healthcare - US

Director of AI

Atlanta, GA · On-site

The Director of AI leads the design, development, and delivery of AI-powered capabilities across ... Guide engineers on best practices for Generative AI, Agentic AI, Retrieval-Augmented Generation ...

Ascent360

Director of AI

Atlanta, GA · On-site

$200 - $250/hr

The Director of AI leads the design, development, and delivery of AI-powered capabilities across ... Guide engineers on best practices for Generative AI, Agentic AI, Retrieval-Augmented Generation ...

Ascent360

Director of AI (Atlanta)

Atlanta, GA · On-site

$243K/yr

The Director of AI leads the design, development, and delivery of AI-powered capabilities across ... Guide engineers on best practices for Generative AI, Agentic AI, Retrieval-Augmented Generation ...

Warnerbros

Staff, Data Science & Applied AI

Atlanta, GA · On-site

... and Direct-to-Consumer platforms. This role is designed for a hands-on expert in applied data ... Generative AI & LLM Applications * Design and implement Generative AI solutions leveraging large ...

C3 AI

Director, Forward Deployed Engineering

Atlanta, GA · On-site

$200 - $250/hr

... generative AI offerings for the enterprise. Learn more at: C3 AI C3 AI's Forward Deployed ... As Director, you will own a portfolio of our most strategic customer relationships end to end, from ...

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Generative Ai Director information

What does a Generative AI Director do?

A Generative AI Director leads teams in developing and deploying artificial intelligence models that create new content, such as text, images, or music. They oversee the strategic vision, project management, and ethical considerations of generative AI initiatives. This role often involves collaborating with data scientists, engineers, and business leaders to ensure AI solutions align with organizational goals and comply with industry standards. Additionally, the Generative AI Director stays up to date with the latest advancements in AI research and guides the integration of cutting-edge technologies into products and services.

What are the key skills and qualifications needed to thrive as a Generative AI Director?

To thrive as a Generative AI Director, you need deep expertise in AI/ML algorithms, experience leading technical teams, and an advanced degree in computer science or a related field. Proficiency with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and familiarity with data privacy standards and relevant certifications (like AWS Certified Machine Learning) are highly valued. Strong leadership, strategic vision, and effective communication skills help drive innovation and align cross-functional teams. These skills are crucial for successfully managing complex AI initiatives, ensuring ethical deployment, and maintaining a competitive edge in a rapidly evolving field.

What are the typical challenges faced by a Generative AI Director when leading cross-functional teams?

As a Generative AI Director, one common challenge is aligning diverse teams—such as data scientists, software engineers, product managers, and designers—toward a unified vision for AI-driven solutions. Balancing innovation with ethical considerations and regulatory compliance is also critical, especially as generative AI evolves rapidly. Additionally, fostering continuous learning while managing stakeholder expectations and resource constraints requires strong leadership, clear communication, and strategic prioritization.

What is the difference between Generative Ai Director vs Data Scientist?

AspectGenerative Ai DirectorData Scientist
Required CredentialsAdvanced degrees in AI, Computer Science, or related fields; leadership experienceBachelor's or Master's in Data Science, Statistics, or related fields; technical skills
Work EnvironmentLeadership roles overseeing AI projects, strategic planning, cross-team collaborationData analysis, model development, statistical modeling, coding
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, e-commerce, research organizations

While both roles involve AI and data, the Generative Ai Director focuses on leading AI initiatives and strategic oversight, whereas the Data Scientist concentrates on data analysis and model development. The Director role typically requires more leadership experience and a broader understanding of AI applications.

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

The most popular types of Generative Ai jobs in Georgia are:

What are popular job titles related to Generative Ai Director jobs in Georgia?

For Generative Ai Director jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Generative Ai Director jobs in Georgia look for?

The top searched job categories for Generative Ai Director jobs in Georgia are:

What cities in Georgia are hiring for Generative Ai Director jobs?

Cities in Georgia with the most Generative Ai Director job openings:

Generative Ai Director jobs near you
Infographic showing various Generative Ai Director 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.

Senior Machine Learning Engineer- Generative AI (REMOTE)

Home Depot

Atlanta, GA • On-site, Remote

$116K - $153K/yr

Full-time

Posted 6 days ago

Home Depot rating

7.4

Company rating: 7.4 out of 10

Based on 6,500 frontline employees who took The Breakroom Quiz

5th of 39 rated national retailers

Job description

With a career at The Home Depot, you can be yourself and also be part of something bigger.
Position Purpose:
The Sr Machine Learning Engineer is responsible for designing, building, integrating, optimizing, and maintaining AI-powered applications that leverage generative models and the overall product lifecycle for a product that our users love. Generative AI Engineers are expected to collaborate closely with teammates as they develop and deliver user stories while supporting AI-powered products as they evolve. Generative AI Engineers may design and implement applications using large language models (LLMs) and other generative models to embed intelligent capabilities directly into software products. Activities may include prompt engineering, model integration, building Retrieval-Augmented Generation (RAG) pipelines, and developing scalable AI services. The role may interact with business stakeholders, infrastructure teams, and development teams to ensure business requirements are effectively addressed through generative AI solutions. The role may also support evaluation, performance optimization, testing, and monitoring of AI systems in production. Additional responsibilities may include working with domain data, improving prompts and AI workflows, and creating documentation or enablement materials for generative AI solutions.
Sr Generative AI Engineers should be able to work independently with minimal guidance, while collaborating with cross-functional teams of varying skill levels to design, deploy, and maintain production AI applications. This role may review submitted code and prompt implementations, providing feedback and improvements based on engineering and responsible AI best practices.
Key Responsibilities:
  • 70% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do "destructive testing" to ensure adequate resiliency in production; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively
  • 10% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations
  • 20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality

Direct Manager/Direct Reports:
  • This Position typically reports to Software Engineer Manager or Sr. Software Engineer Manager
  • This Position has 0 Direct Reports

Travel Requirements:
  • Typically requires overnight travel 5% to 20% of the time.

Physical Requirements:
  • Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:
  • Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:
  • Must be eighteen years of age or older.
  • Must be legally permitted to work in the United States.

Preferred Qualifications:
  • 3 - 5 years of relevant work experience
  • Experience in Python and modern AI development frameworks
  • Experience building Generative AI applications using large language models (LLMs)
  • Experience with prompt engineering, prompt optimization, and prompt evaluation techniques
  • Experience integrating AI models through APIs from platforms such as Google, OpenAI or Anthropic
  • Experience with GenAI frameworks such as Google Agent Development Kit (ADK)
  • Experience implementing Retrieval-Augmented Generation (RAG) pipelines using vector databases
  • Experience working with vector databases such as google Vertex AI Search
  • Experience with building conversational AI systems, or AI assistants
  • Experience with responsible AI practices including bias mitigation and safety guardrails
  • Experience working with graph databases, knowledge ingestion pipelines, and data mesh architectures to enable scalable, connected, and queryable AI knowledge systems.
  • Experience implementing CI/CD pipelines, monitoring, and automated workflows for reliable AI model deployment and lifecycle management.
  • Experience with monitoring, evaluation, and optimization of production AI systems
  • Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc- Experience in a modern scripting language (preferably Python)
  • Experience with GPU acceleration (i.e. CUDA and cuDNN)
  • Experience in a front-end technology and framework such as Node.js, HTML, CCS, JavaScript, ReactJS, D3
  • Experience in writing SQL queries against a relational database
  • Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security
  • Familiarity with cloud computing platform and associated automation patterns and machine learning services they provide
  • Familiarity with defensive coding practices and patterns for high Availability
  • Familiarity with A/B testing and effective REST design for scalable web services architecture
  • Familiarity with advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization

Minimum Education:
  • The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.

Preferred Education:
  • No additional education

Minimum Years of Work Experience:
  • 2

Preferred Years of Work Experience:
  • No additional years of experience

Minimum Leadership Experience:
  • None

Preferred Leadership Experience:
  • None

Certifications:
  • None

Competencies:
  • Global Perspective
  • Manages Ambiguity
  • Nimble Learning
  • Self-Development
  • Collaborates
  • Cultivates Innovation
  • Situational Adaptability
  • Communicates Effectively
  • Drives Results
  • Interpersonal Savvy

What Home Depot employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Home Depot logo

About Home Depot

Sourced by ZipRecruiter

The Home Depot is the world’s largest home improvement specialty retailer, operating a vast network of warehouse-format stores across the United States, Canada, and Mexico. Founded in 1978, the company has established itself as the primary resource for building materials, lawn and garden products, and home décor. Its business model caters to two distinct customer bases: Do-It-Yourself (DIY) homeowners and "Pro" customers, such as professional contractors and tradespeople. Beyond product sales, the company offers an extensive suite of services, including professional installation and one of the largest tool rental operations in North America.

Industry

Retail, manufacturing and personal services

Company size

10,000+ Employees

Headquarters location

Atlanta, GA, US

Social media

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