7 Generative AI Roles and How to Get Started

Written by Coursera Staff • Updated on

Discover the most sought-after roles in generative AI and learn what it takes to start a career in this field.

[Feature Image] A person performs their duties while working in a generative AI role for a company.

Key takeaways

Roles in generative AI include prompt engineer, AI trainer, data scientist, AI designer, AI developer, and machine learning engineer. 

  • A type of deep learning model, generative AI can generate text, computer code, multimedia content, and more.

  • Launching your career in this field starts with enrolling in a degree program, earning relevant certifications, and gaining experience with generative AI tools. 

  • You can use Gen AI to summarize documents in project management, refresh existing marketing content, forecast customer demand, and detect and troubleshoot bugs during product development. 

Explore popular generative AI roles and discover how to take the first steps toward starting a career in this field. If you’re ready to begin building your generative AI skill set, enroll in the Generative AI Fundamentals Specialization offered by IBM. In as little as four weeks, you can learn about large language modeling, deep learning, prompt engineering, and generative model architectures. 

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, GenAI 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 GenAI. As an evolving technology, GenAI 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 GenAI to alter or refresh their existing content.

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

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

Read more: What Is Generative AI? How It Works, Examples, Benefits, and Limitations

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 20 percent through 2034 [1]. Much of this growth is due to increased demand for automation and machine learning technologies like AI. Furthermore, according to a 2025 McKinsey global survey, 71 percent of respondents reported regular use of Gen AI in their organizations, up from 65 percent at the beginning of 2024 [2].

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

All salary information represents the median total pay from Glassdoor as of June 2026. These figures include base salary and additional pay, which may represent profit-sharing, commissions, bonuses, or other compensation.

1. Prompt engineer

Median annual total salary: $131,000 [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 and Gemini (formerly Bard). 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

Median annual total salary: $81,000 [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. Daily tasks can involve designing data sets, running simulations, and improving training methodologies. You might also contribute to the evolution of AI systems, such as natural language understanding (NLU), data science, and generative AI models, that continue to converge. 

3. Data scientist

Median annual total salary: $156,000 [5]

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

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

4. AI designer

Median annual total salary: $108,000 [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 

Median annual total salary: $160,000 [7]

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

As an AI developer, you combine your programming, data science, and machine learning skills to create AI systems capable of automating tasks that usually require 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

Median annual total salary: $163,000 [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. You might also explore GenAI platforms like H2O.ai as part of your development strategy. Furthermore, training algorithms on fresh data enables them to learn and improve, allowing for higher accuracy in performing tasks over time. 

7. Natural language processing (NLP) engineer 

Median annual total salary: $165,000 [9]

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

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

What 5 jobs will survive AI?

Five jobs that may survive AI are financial examiners, information security analysts, operations research analysts, makeup artists, and electricians. Health care roles that might withstand AI include nurse practitioners, physical therapists, dentists, home health aides, medical assistants, nutritionists, and mental health counselors.

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 daily. If you aim to start a career in this field, the tips below can help you build a strong foundation. 

Enroll in a degree program.

Many 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 using prompts to generate a product description for an e-commerce website, develop subject lines for marketing purposes, or create a plan for a project.

Explore our free generative AI resources

Subscribe to our Career Chat newsletter on LinkedIn for industry insights, skill-building tips, and networking opportunities. Then, explore our free resources for learning more about generative AI:

Whether you want to develop a new skill, get comfortable with an in-demand technology, or advance your abilities, keep growing with a Coursera Plus subscription. You’ll get access to over 10,000 flexible courses. 

Article sources

1. 

US Bureau of Labor Statistics. “Computer and Information Research Scientists, https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm.” Accessed June 22, 2026.

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