7 Generative AI Roles and How to Get Started

According to a global survey by McKinsey in 2024, 65 percent of respondents indicated regular use of generative artificial intelligence (AI) in their organizations, almost twice the level reported in 2023 [1]. The survey also revealed that businesses primarily apply generative AI in two key areas: “marketing and sales” and “product and service development” [1].

As generative AI gains rapid acceptance in the workplace, job prospects in the field are growing just as fast. Explore popular generative AI roles and discover how to take the first steps toward starting a career in this field.

course

Generative AI: Impact, Considerations, and Ethical Issues

In this course, you will explore the impact of generative artificial intelligence (AI) on society, the workforce, organizations, and the environment. This ...

4.7

(185 ratings)

14,145 already enrolled

Beginner level

Learn More

Average time: 6 hour(s)

Learn at your own pace

What is gen AI?

Gen AI (or genAI), short for generative AI, aids in producing various types of content based on prompts. A type of deep learning model, gen AI can generate text, computer code, multimedia content, and more. OpenAI’s ChatGPT, a chatbot trained to interpret prompts and provide comprehensive responses, is a prime example of gen AI. As an evolving technology, gen AI benefits enterprises in several ways, with use cases including but not limited to:

• Project management: Using generative AI, project managers can quickly generate summaries of key business documents, saving time for more critical tasks.

• Marketing: Generative AI helps strengthen marketing campaigns through personalized communication across customer touchpoints. Additionally, brands may use gen AI to alter or refresh their existing content.

• Sales: When combined with machine learning, generative AI can help businesses forecast customer demand with greater accuracy, potentially boosting sales performance.

• Product development: With gen AI, businesses can develop preliminary code for upcoming product features, lightening the load on product teams. Developers can also use gen AI to detect and troubleshoot bugs. 

7 in-demand generative AI roles

The demand for generative AI jobs and related technologies is soaring, with many offering high salaries. The US Bureau of Labor Statistics (BLS) projects employment of computer and research information scientists, including AI roles, to grow by 26 percent through 2033 [2]. Much of this growth is due to increased demand for automation and machine learning technologies like AI.

Below are some popular generative AI roles and their salaries, as reported by Glassdoor. 

1. Prompt engineer

Average annual salary: $135,336 [3]

Education requirements: Bachelor’s degree in computer science, linguistics, engineering, or a related field

As a prompt engineer, you will specialize in creating and refining text-based instructions, also known as prompts, used by generative AI models like ChatGPT, Gemini (formerly Bard), and DALL-E. In addition, you’ll work toward evaluating prompt performance. Based on your firm’s business goals, you may also use telemetry data to maintain a customized library of prompts.

2. AI trainer

Average annual salary: $73,084 [4]

Education requirements: Master’s degree in computer science, data analytics, machine learning, or a similar field

As an AI trainer, you’ll help build AI systems that accurately interpret and respond to human input. Your daily tasks can involve designing data sets, running simulations, and improving training methodologies. You might also contribute to the evolution of AI systems as natural language understanding (NLU), data science, and generative AI models continue to converge. 

3. Data scientist

Average annual salary: $117,664 [5]

Education requirements: Bachelor’s degree in computer science, data analysis, mathematics, or a related field

In your role as a data scientist, you will harness advanced tools to draw actionable insights from big data. Essentially, you discover trends, evaluate patterns, and establish relationships within data. You may also use generative AI to support predictive analytics.

4. AI designer

Average annual salary: $99,582 [6]

Education requirements: A degree in computer science or other pertinent fields, and you may also take courses on AI and UX design 

In the AI designer role, you’ll merge the technical side of AI with the creative elements of user experience (UX) design. Your primary focus is to create intuitive interfaces for AI applications. You might also use generative AI to produce multiple design prototypes to facilitate rapid testing and refinement.

5. AI developer 

Average annual salary: $106,563 [7]

Education requirements: Bachelor’s degree in computer science, engineering, data science, or a similar discipline 

As an AI developer, you combine your skills in programming, data science, and machine learning to create AI systems capable of automating tasks that usually need human effort. Mainly, you work on integrating AI algorithms into software projects. You may also use generative AI to simplify tasks such as code documentation. 

6. Machine learning engineer

Average annual salary: $122,461 [8]

Education requirements: Bachelor’s degree in computer science, software engineering, mathematics, or a related field

As a machine learning engineer, you design algorithms for distinct tasks such as classification, forecasting, and prediction. As part of your development strategy, you might also explore gen AI platforms like H2O.ai. Furthermore, by training algorithms on fresh data, you enable them to learn and improve, allowing for higher accuracy in performing tasks over time. 

7. Natural language processing (NLP) engineer 

Average annual salary: $123,212 [9]

Education requirements: Bachelor’s degree in computer science, linguistics, or a similar field

As an NLP engineer, your role is crucial for integrating gen AI into an organization. Your expertise lies in natural language processing (NLP), a discipline that blends computer science, AI, and linguistics. You’ll work toward developing chatbots and virtual assistants, among other gen AI tools that interact with users in real-time.

How to launch your career in generative AI

Amazon, Meta, and Netflix are among the top-paying companies for generative AI professionals, but more companies are adopting AI every day. If you’re aiming to start a career in this field, the tips below can help you build a strong foundation. 

Enroll in a degree program.

Most employers set a bachelor's degree as the minimum education requirement for generative AI jobs, with common majors including computer programming, information technology, software engineering, and data science. To further strengthen your expertise, you may consider obtaining a master’s degree. Pursuing an advanced degree can also pave the way for a higher income. 

Obtain relevant certifications.

Certifications can help you stay current with industry trends and demonstrate your commitment to professional growth. The following are some certifications you can target based on your career goals:

• Generative AI Foundation Certification

• Certified Generative AI Specialist (CGAI)

• Certified Prompt Engineer

• Microsoft Certified: Azure AI Engineer Associate

Gain hands-on experience with gen AI tools.

The more experience you gain with generative AI tools, the more efficient you become at using them. Additionally, working directly with generative AI tools helps you understand how they can be useful in real-world scenarios, which can, in turn, enhance your problem-solving skills. For example, you could practice how to use prompts to generate a product description for an e-commerce website, develop subject lines for marketing purposes, or create a plan for a project.

Learn more about generative AI on Coursera

Generative AI, with deep learning at its core, helps produce various forms of content, including images, code, text, and video, in response to specific prompts. Discover the techniques and best practices for writing effective prompts in IBM’s Generative AI Fundamentals Specialization.

This specialization includes courses like Generative AI: Impact, Considerations, and Ethical Issues, which can help you gain insights into the ethical concerns surrounding generative AI, including data privacy, biases, and copyright infringement.

specialization

Generative AI Fundamentals

Unlock and leverage the potential of generative AI. Learn how you can use the capabilities of generative AI to enhance your work and daily life.

4.7

(872 ratings)

31,106 already enrolled

Beginner level

Learn More

Average time: 1 month(s)

Learn at your own pace

Skills you'll build:

Artificial Intelligence (AI), Prompt Engineering, ChatGPT, hugging face, Generative AI Careers, Generative AI, Stable Diffusion, Hugging Face, Foundation Models, Responsible Generative AI, Limitations of Generative AI, Impact of Generative AI, Ethics in Generative AI, Business Transformation, Career Opportunities, AI empowered workplace, Career Enhancement, prompt patterns, Large Language Models (LLM), Pre-trained Models, Natural Language Generation

course

Generative AI: Impact, Considerations, and Ethical Issues

In this course, you will explore the impact of generative artificial intelligence (AI) on society, the workforce, organizations, and the environment. This ...

4.7

(185 ratings)

14,145 already enrolled

Beginner level

Learn More

Average time: 6 hour(s)

Learn at your own pace