Generative AI Job Description

Generative artificial intelligence (AI) can potentially change how industries operate by automating tasks and increasing productivity. Generative AI professionals help organizations train models, optimize workflows, and streamline designs. According to Grand View Research, “The global generative AI market size was valued at USD 16.87 billion in 2024 and is projected to grow at a CAGR of 37.6 percent from 2025 to 2030.” [1]

Whether you're in the market looking for a job related to generative AI or planning to hire someone, knowing what to expect in a job description is helpful. Expand your knowledge of generative AI job descriptions and discover the skills and experience necessary to excel in the industry.

course

Generative AI for Everyone

Instructed by AI pioneer Andrew Ng, Generative AI for Everyone offers his unique perspective on empowering you and your work with generative AI. Andrew will ...

4.8

(3,242 ratings)

525,089 already enrolled

Beginner level

Learn More

Average time: 5 hour(s)

Learn at your own pace

Skills you'll build:

Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), OpenAI, Ethical Standards And Conduct, Data Ethics, Business Process Automation, Machine Learning, Cost Estimation, ChatGPT, Cloud Applications, Feasibility Studies, Market Opportunities, Reinforcement Learning, Job Analysis, Business Economics, Generative AI

What is generative AI?

Generative AI refers to a set of deep learning models designed to create text, images, and other various forms of content. These models try to produce results independently without human intervention to replicate human ideas.

Types of generative AI roles and responsibilities 

If you're looking to enter the AI field, there are various specialized roles available, including: 

• Generative AI engineer: Create, refine, and streamline algorithms for generative AI models utilizing deep learning.

• Machine learning scientist: Design and develop AI algorithms for software, ensuring the model generates accurate and reliable predictions.

• Generative AI marketer: Leverage AI-generated content to conceptualize new marketing techniques. Edit and personalize social media posts and blog articles with AI.  

• Data scientist: Leverage generative AI agents to streamline data processing tasks and optimize workflows. The data will also be used to develop and train models. 

Essential generative AI skills

Specific skills are often required to excel in generative AI roles, including proficiency in key programming languages and experience with machine learning frameworks and generative modeling techniques. Here are the essential skills needed to succeed in your AI role:

Programming languages

• Python: The most widely used language in machine learning and data science, used to fine-tune generative AI models and analyze data.

• C++: Popular for writing efficient programs for AI models.

• R: Excels in statistical and data analysis, useful for finding patterns and developing insights from model outputs.

Machine Learning Frameworks

• TensorFlow: Used to build and train generative AI models, performing machine learning tasks efficiently.

• PyTorch: Helps optimize model memory and condense datasets for manageable sizes.

Generative Modeling Techniques

• Generative Adversarial Networks (GANs): Comprise generators that create hyper-realistic images and discriminators that decide if the images are fake or real.

• Variational Autoencoders (VAEs): Creates new data similar to input training datasets in machine learning.

Qualifications and experience requirements

Generative AI roles often require a bachelor’s or master’s degree in fields like data science, computer science, statistics, and information technology (IT). A relevant major is crucial to learning the skills and foundations of AI through its coursework.

Various online courses and certification programs in machine learning, deep learning, and AI are also available. Attending conferences and workshops related to AI could also help you broaden your understanding and build your network within the field. 

Earn Your Degree

Master of Applied Data Science

from the University of Michigan

100% ONLINE

Master of Science in Data Analytics Engineering

from Northeastern University

100% ONLINE

Master of Data Science

from the University of Pittsburgh

100% ONLINE

• 1
• 2

You are Currently on slide 1

Key competencies for success

As an AI professional, you bring the important element of humanity to your work. For this reason, demonstrating the following important competencies is essential in your career: 

• Design thinking: Implement human-centered problem-solving skills when building AI models and execute intuitive approaches to make the tool more accessible to the user. 

• Adaptability and reliability: Maintain the ability to adapt to your work environment and learn and grow from your mistakes. You must meet deadlines, obtain your goals, and hold yourself accountable.

• Work with interdisciplinary teams: Learn from and listen to your mentors, leaders, and coworkers. 

• Ethical considerations: Ensure you consider ethics and address ethical issues while training generative AI models. 

• Emotional intelligence: Understand and manage your emotions, and resolve issues while remaining empathetic. 

A well-rounded approach to training AI models is important for generative AI professionals. While technical training is essential, integrating workplace skills into your professional life can help you excel in the generative AI industry.

Industry variations in the generative AI job description

Various industries have adopted generative AI, including health care, marketing, manufacturing, and legal services. These roles vary within each industry, here are some examples:

• Health care: You may participate in drug discoveries, genomics, or clinical trials that leverage AI in your research.

• Marketing: As a marketer, you may edit and personalize AI-generated content or optimize AI-generated advertisements.

• Manufacturing: You may use generative AI predictive analytics to streamline processes. 

Learn more about generative AI with Coursera

Generative AI is a rapidly growing field that evolves as AI becomes more prevalent in various industries. Explore the expanding potential of generative AI and discover more about how it works on Coursera. Consider DeepLearning.AI’s Generative AI for Everyone, or learn more about the various applications of generative AI across different industries with IBM’s AI Foundations for Everyone Specialization. Upon completing either program, gain a shareable certificate to include in your resume, CV, or LinkedIn profile.

course

Generative AI for Everyone

Instructed by AI pioneer Andrew Ng, Generative AI for Everyone offers his unique perspective on empowering you and your work with generative AI. Andrew will ...

4.8

(3,242 ratings)

525,089 already enrolled

Beginner level

Learn More

Average time: 5 hour(s)

Learn at your own pace

Skills you'll build:

Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), OpenAI, Ethical Standards And Conduct, Data Ethics, Business Process Automation, Machine Learning, Cost Estimation, ChatGPT, Cloud Applications, Feasibility Studies, Market Opportunities, Reinforcement Learning, Job Analysis, Business Economics, Generative AI

specialization

AI Foundations for Everyone

Unlock your potential with AI. Build job-ready AI skills to enhance your career. Everyone welcome. No prior AI background required.

4.7

(3,797 ratings)

45,354 already enrolled

Beginner level

Learn More

Average time: 1 month(s)

Learn at your own pace

Skills you'll build:

Large Language Models (LLM), Generative AI, Natural Language Generation, Artificial Intelligence (AI), ChatGPT, WordPress, IBM Cloud, watsonx Assistant, Customer Service, Chatbot Building, AI Fundamentals, Natural Language Processing, AI ethics, Machine Learning, Artificial Intelligence, Prompt Engineering, prompt patterns