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Ai Manager Jobs in South Fulton, GA (NOW HIRING)

Florence Healthcare

AI Automation Manager

Atlanta, GA · On-site

They are seeking an AI Automation Manager to lead the company's AI transformation efforts, focusing on identifying, applying, and scaling AI-driven improvements across operations. Responsibilities ...

Spruce Infotech

AI SDLC Program Manager

Atlanta, GA · On-site

AI SDLC Program Manager Start date* 17-Aug-26 End date* 16-Feb-27 Number of Positions* 1 * We are looking for a strong Program Manager to lead an AI-enabled SDLC platform/program for one of our ...

Workday

Engagement Manager, AI Practice

Atlanta, GA

As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most. The ...

SupplyHouse

Technical Product Manager - AI

Atlanta, GA

$116K - $146K/yr

We are looking for a Technical Product Manager - AI to join our Product, Systems, and Insights Team. This individual will report into our Senior Director, PSI and will own the strategy and execution ...

KPMG

Manager, AI Engineer

Atlanta, GA · On-site

Manage AI projects including architecture design, model development, integration, and testing, and ensure projects follow best practices in MLOps, security, compliance, and scalability to support ...

Mwe

Senior Manager, AI & Analytics

Atlanta, GA · On-site

The Senior Manager, AI & Analytics owns the Accounting & Finance Systems Reporting, Data & AI Center of Excellence - driving strategy, governance, and delivery of analytics, intelligent automation ...

YO AI Labs

AI Consulting Expert - Remote

Atlanta, GA · Remote

$100 - $200/hr

Job Title: AI Consulting Domain Remote Job Type: Contractor (Part-Time) Location: Remote Job ... management consulting, corporate strategy, business transformation, or operations. * Experience ...

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Ai Manager information

What does an AI manager do?

An AI Manager oversees the development, implementation, and optimization of artificial intelligence solutions within an organization. They lead AI teams, manage projects, and ensure alignment with business goals while addressing technical and ethical concerns. AI Managers collaborate with data scientists, engineers, and executives to drive innovation and improve operational efficiency. They also stay updated on industry trends and advancements to leverage AI effectively.

What are the key skills and qualifications needed to thrive as an AI manager?

To thrive as an AI Manager, you need a strong background in computer science, machine learning, project management, and proven experience leading AI initiatives, often supported by a relevant degree or industry certifications. Familiarity with AI frameworks and tools such as TensorFlow, PyTorch, cloud platforms, and knowledge of data governance and MLOps is commonly required. Excellent leadership, problem-solving, and communication skills help AI Managers effectively coordinate cross-functional teams and translate business objectives into actionable AI solutions. These competencies are essential for successfully driving AI projects from conception to deployment while aligning with organizational goals.

What types of teams or departments does an AI manager typically collaborate with?

AI Managers work closely with data scientists, software engineers, product managers, and business stakeholders to ensure AI projects align with company objectives. They often coordinate with IT teams for infrastructure requirements, as well as legal and compliance teams regarding data privacy and ethical AI practices. Close collaboration with these groups helps deliver robust and scalable AI solutions, fostering a multidisciplinary approach that enhances project success. By acting as a bridge between technical and non-technical teams, AI Managers ensure that business needs are clearly understood and translated into effective AI strategies.

How do you become an AI manager?

To become an AI manager, candidates typically need a strong background in computer science, data science, or related fields, along with experience in AI and machine learning projects. Developing skills in programming languages like Python, understanding AI tools and frameworks, and obtaining relevant certifications can enhance qualifications. Leadership and project management skills are also important for overseeing AI teams and initiatives.

How much does an AI manager make?

An AI manager's salary typically ranges from $100,000 to $180,000 annually, depending on experience, location, and industry. Senior AI managers with specialized skills in machine learning and data analysis can earn higher compensation, often supplemented with bonuses and stock options.

What is the role of an AI manager?

An AI manager oversees the development, implementation, and maintenance of artificial intelligence projects within an organization. They coordinate teams of data scientists and engineers, ensure project goals align with business objectives, and often require knowledge of machine learning tools and programming languages. Their role involves strategic planning, resource management, and ensuring ethical AI practices.

What job categories do people searching Ai Manager jobs in South Fulton, GA look for?

The top searched job categories for Ai Manager jobs in South Fulton, GA are:

What cities near South Fulton, GA are hiring for Ai Manager jobs?

Cities near South Fulton, GA with the most Ai Manager job openings:

Ai Manager jobs near you
Infographic showing various Ai Manager job openings in South Fulton, GA as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

AI Project / Delivery Manager

Staff Financial Group

Atlanta, GA • Hybrid

$135K - $175K/yr

Full-time

Re-posted 10 days ago

Job description

AI Project / Delivery Manager - Atlanta, GA (Hybrid)

About the Role

We are seeking an experienced AI Project / Delivery Manager to lead the planning, execution, and successful delivery of artificial intelligence and machine learning initiatives across the enterprise.

This role bridges the gap between technical implementation and business impact—ensuring AI projects are delivered on time, within scope, and aligned with strategic objectives. The ideal candidate combines strong project management skills, a working knowledge of AI/ML concepts, and the ability to communicate effectively across technical and non-technical teams.

Key Responsibilities

  • Project Ownership: Oversee the full lifecycle of AI projects—from initiation and business case development through deployment and post-implementation review.
  • Cross-Functional Leadership: Partner with Data Science, Engineering, Product, and Business Units to define scope, success criteria, and resource requirements.
  • Delivery Management: Lead agile delivery processes, manage sprint planning, backlogs, and daily standups for AI teams.
  • Stakeholder Communication: Translate complex technical topics (LLMs, MLOps, NLP, computer vision) into clear business value and deliver progress updates to executives.
  • Risk & Quality Management: Identify and mitigate delivery risks related to data, security, or performance. Ensure adherence to DevSecOps, governance, and compliance standards.
  • Vendor & Platform Coordination: Manage third-party AI vendors, SaaS integrations (e.g., AWS SageMaker, Azure AI, OpenAI, or Vertex AI), and platform implementations.
  • Metrics & Reporting: Establish KPIs to track model adoption, ROI, and delivery efficiency.
  • Change Enablement: Support user adoption and training programs for AI-powered tools across departments.

Required Qualifications

  • 5+ years of experience managing software, data, or AI-related projects.
  • Proven experience leading Agile or Scrum delivery teams in a technical environment.
  • Strong understanding of AI/ML fundamentals and lifecycle management (data prep, model training, deployment).
  • Familiarity with cloud AI ecosystems (AWS SageMaker, Azure AI, or Google Vertex AI).
  • Experience working with DevOps or MLOps frameworks.
  • Demonstrated ability to manage multiple concurrent initiatives in complex enterprise environments.
  • Excellent communication, stakeholder management, and executive presentation skills.