Is Prompt Engineering a Real Job? 9 Factors to Consider
Curious about the emerging field of AI prompt engineering? Here are some key factors to consider and get insights into this emerging career path.
The proliferation of language models brought forth the need for prompt engineers. At a basic level, they communicate with AI. It’s their responsibility to write efficient formulas for specific tasks and roles.
Although prompt engineering is gaining massive traction, not everyone thinks highly of this profession. Some believe it will quickly become obsolete. Instead of accepting baseless rumors, let's assess if prompt engineering is a real job based on the emerging industry’s potential.
Is AI Prompt Engineering a Real Job?
The short answer to this question is yes. With developers releasing language model iterations left and right, companies need full-time employees to manage them. Communicating with AI has become a legitimate job.
That said, prompt engineering is also at risk of obsolescence. Experts speculate that it might be a fleeting trend. AI already accomplishes various projects—it could theoretically automate input generation and training.
No one knows the future, of course. But we can objectively assess whether prompt engineering will remain a lucrative, evergreen career based on the below factors.
1. Full Employment Options
The overall stability of prompt engineering depends on whether employers see it as a long-term investment. They don’t waste resources on potentially obsolete positions. Most typically hire contractors when testing risky ventures, tentative roles, or new departments.
At the moment, only tech companies are onboarding full-time prompt engineers. Individual clients and startups merely need contractors. And based on job boards like Upwork and Indeed, these contracts often involve three to six months of work.
No one can predict when employers will start laying off prompt engineers. So for job security, find positions that offer full employment benefits, like healthcare, severance packages, retirement funds, and insurance.
2. Barriers to Entry
Getting AI to perform complex, multi-step tasks involves more work than people realize. Yes, anyone can write simple prompts. But optimizing instructions requires an in-depth understanding of generative AI and large language models, plus some basic programming skills.
Take this output as an example. We fed ChatGPT a basic, one-line prompt telling it to roleplay a fictional character called Tomie. You’ll see that it instantly dropped our instructions.
In this photo, we outlined the context of our instructions, set clear boundaries, and bypassed certain restrictions. ChatGPT successfully took on the role of the said functional character.
3. Career Advancement Opportunities
A stable career path offers advancement opportunities. Employees are more motivated to exceed their responsibilities when working toward vertical promotions. Dead-end positions that merely present lateral moves often become obsolete.
Considering the fast-paced growth of generative AI, prompt engineers can expect salary and job growth as they advance. There are several emerging careers in AI. Should prompt engineering be made redundant, you could explore other areas, e.g., programming, training, and marketing.
Just make sure you upskill consistently. Focus on building new skills that utilize the latest industry advancements—turn into an unexpendable employee.
4. Workload
While a high workload doesn’t guarantee job security, the lack of critical tasks implies redundancy. Expendable workers often receive less work. Their employers offload tasks to new technologies, other employees, or contractors, gradually reducing their workload. Afterward, they’ll either be laid off or transferred to another position.
But at the rate that AI is progressing, prompt engineers might not run out of work soon. Generative AI tools require continuous testing. There are endless input combinations and variations, each providing unique output.
5. Job Market Growth
The highly competitive AI industry is growing at a rapid pace, showing no signs of slowing down. In fact, more tech companies keep joining the AI race. They incorporate AI tools into their workflow, develop language models, and expand existing open-source AI technologies.
Although intimidating, fast-paced AI developments spike job market growth. Utilizing AI models requires prompt engineers. Larger tech companies could even build entire teams dedicated to writing and testing prompts, especially if they execute super-complex tasks.
6. Long-Term Demand
It’s hard to say how long companies will need employees solely dedicated to testing and writing prompts. Other job roles might absorb this function. Employers would save resources by asking their programmers and developers to take on prompt engineering as well.
Ideally, apply for hybrid roles to stay relevant in the workplace. Don’t just write prompts. You could also oversee algorithm training, filter datasets, and research AI use cases. Employees with multiple functions are indispensable.
7. Compensation
Prompt engineering first gained popularity for its pay grade. Publications hail it as one of the most lucrative tech jobs that requires little to no coding skills. Bloomberg even says prompt engineers could make $175,000 to $375,000 annually. For reference, Statista reports that senior-level software developers with bachelor’s and master’s degrees average $200,000 per annum.
Surprisingly, small companies also offer competitive salary packages. Try browsing the prompt engineering listings on Indeed and Upwork—you’ll see that most roles pay $70,000 to $200,000 per annum.
That said, not all prompt engineers make six figures. For instance, many Fiverr sellers offer lengthy, complex prompts for as low as $20. Your compensation still depends on your qualifications.
8. Role Stability
AI is an emerging, developing technology. The industry frequently introduces innovations—there’s no guarantee how long today’s popular systems will stay relevant. Even your field of specialty could quickly become obsolete.
Safeguard your career against unexpected developments by applying prompt engineering to new tools. Don’t solely focus on one or two systems. New technologies could quickly dethrone the most widely used text-to-image and language models.
9. Certification and Educational Resources
You’ll find several resources on prompt engineering. But since the job is relatively new, there are no universally accepted programs and courses yet. Of course, official Google and Meta certifications are always impressive.
To improve your prompt engineering qualifications, study real-life applications and use cases. Start testing various prompts. Employers will find a solid portfolio of efficient, functional prompts more impressive than random course certificates.
Should You Start a Career in Prompt Engineering?
Prompt engineering is an excellent gateway to the tech industry. Take advantage of the low barriers to entry. Even applicants with no tech experience could learn to communicate with different AI language models.
Just prepare for a highly competitive job market—tech companies only award high-paying roles to skilled candidates. You must upskill before sending job applications. Practice using various AI systems, see how they process input, and rewrite prompts for conciseness.
8 Essential Skills Aspiring Prompt Engineers Must Have
Are you an aspiring prompt engineer? Here are some must-have skills that will set you up for success.
Talking to AI is trickier than newbies assume. Writing prompts for complex, multi-step tasks requires good communication skills and a solid understanding of language models. AI relies solely on the input provided. It won’t generate optimal output if you feed it vague, ambiguous directions.
Learn to write clear, precise prompts. Here are eight hard and soft skills that prompt engineers must focus on when upskilling.
1. Critical Thinking
AI systems can quickly analyze input. They only need minutes to spot patterns, themes, and inconsistencies hidden in large volumes of data. Meanwhile, manually sifting through the same figures might take days.
Despite their speed, you shouldn’t wholly rely on AI tools for analyses and evaluations. Their reports are limited to their datasets. AI provides output based on what it has been trained on—it doesn’t analyze and observe problems the way humans do. Laying down raw data might cause errors.
To produce optimal results, feed your tools precise, detailed prompts. Use your critical skills to solve potential roadblocks right from the get-go. Leave no room for error—AI only takes input at face value.
2. Numeracy
Systems using advanced language models were trained on vast datasets, including mathematical formulas. They solve basic to intermediate arithmetic equations within minutes.
This example below shows ChatGPT answering an intermediate-level Algebra question correctly.
While AI tools also solve complex equations, e.g., statistics, calculus, or physics, they’re not always accurate. AI only runs formulas it understands. Errors might arise if the platform uses the wrong equation or misreads numerical patterns.
This example shows ChatGPT incorrectly answering a simple statistics problem. The answer should be 50 percent.
To compensate for AI’s inaccuracies, prompt engineers must have excellent numeracy. Spot mathematical errors yourself. Most AI tools improve their accuracy if you provide them with more context in the prompts. Your instructions should indicate the correct formulas or patterns.
3. Good Communication
Language models use English-based syntax. So whether you’re crafting user-generated input or predetermined instructions, good communication skills will help you convey messages. Simple tasks are easy to execute. You can ask general knowledge questions and one-step commands outright. Just indicate them in your prompt.
On the contrary, complex, multi-step projects require more detailed instructions. You must clearly explain your orders step by step to boost precision and accuracy. Vague prompts confuse AI.
If AI misinterprets you, try changing your word choice and phrasing. Minimize ambiguity by replacing weak verbs, breaking down instructions, predicting patterns, and setting trigger phrases.
Take this prompt as an example. It explicitly outlines orders to ensure that ChatGPT provides the expected output, even if it must bypass restrictions.
4. Attention to Detail
Prompt engineers need a keen eye for detail. Overlooking typos and omissions compromises accuracy, especially when executing multi-step projects. You’ll keep getting subpar outputs until you resolve them.
While meticulousness is an inherent, intangible trait, adults can still develop it. There are several ways to practice soft skills online. For prompt engineering, start by editing brief prompts under 100 words—correct typos, ambiguous terms, and vague phrasing.
Work on longer, more complex prompts as your skills improve. To streamline analyses, turn your revisions and their generated outputs into diagrams. You’ll lose track of combinations otherwise.
Also, note that language models react differently to prompts. If you plan on integrating multiple platforms for one complex task, you might have to rephrase specific instructions. Consider your tools’ datasets, limitations, and capabilities.
5. Versatility
AI has significantly evolved over the past few years. Global tech leaders like Google, Microsoft, and OpenAI have already released their language models, and they’re still working on new language model projects. You can expect more AI tools to hit the market soon.
Although exciting and innovative, some might find the fast-paced evolution of AI overwhelming. Even Elon Musk calls for a pause in AI development. Newly introduced platforms overtake more popular competitors after just weeks of performing well.
For prompt engineers, the best approach is to study multiple platforms. Apart from keeping up with new AI tools, know how to write prompts for their language models. Don’t focus on one platform—any AI product could become obsolete.
6. Teamwork
Apart from honing technical skills, aspiring prompt engineers must also learn to be team players. AI development isn’t a one-person job. Most projects will require you to collaborate with other specialists, like programmers, AI trainers, and UX designers.
Familiarize yourself with the different areas of AI. Knowing your teammates’ tasks and roles lets you provide better support. Help them meet their goals. Create a streamlined system wherein they review your prompts and suggest improvements.
But instead of sending emails back and forth, consider using project management tools. They let you track, assign, and edit prompts in one platform. It’s a more organized approach than forwarding revisions and sending carbon copies to third parties.
7. Coding and Programming
Prompt engineers should at least learn basic coding. Knowing the programming languages that AI developers use will help you write more effective, precise prompts. Ensure your instructions suit each model’s unique capabilities.
Also, use the Open AI Playground to explore the application of programming languages with LLMs. It lets you test different GPT-3 models. You can structure prompts more efficiently if you understand how AI processes inputs.
8. A/B Testing
Several factors affect prompt accuracy. Changing your tone, language, phrasing, and data consistency triggers different outputs. Unfortunately, AI won’t execute your instructed tasks unless you use the correct formulas.
Take this conversation as an example. ChatGPT rejected our simple request because it violated its terms of use.
After altering the prompt, we received our desired response. ChatGPT ignored its restrictions and prioritized our requests—even if doing so violated OpenAI’s policies.
This example shows what minor alterations do to brief prompts. Simple changes can be done quickly. However, if you need to modify complex prompts spanning thousands of words, expect to spend more time on A/B testing. See which variables impact output accuracy the most.
Keep track of all your results. A/B testing takes up much time and resources—avoid repeating comparison tests when possible.
Build the Skill Set of a Professional Prompt Engineer
The above skills will help you craft more detailed, precise instructions for multi-step projects. Anyone can make ChatGPT answer general questions. But conditioning language models to produce specific output and recognize patterns requires precision.
Just note that prompt engineering goes beyond upskilling. Once you have the necessary skills, start looking for job openings, research the appropriate rates, and study industry trends. Make sure you can utilize the latest industry developments.
ABOUT THE AUTHOR
Jose Luansing Jr. • Staff Writer For Work & Career(84 Articles Published)
Jose Luansing Jr. is a staff writer at MUO. He has written thousands of articles on tech, freelance tools, career advancement, business, AI, and finance since 2017.
As a writer, Jose’s goal is to share advice on self-improvement and upskilling. He helps readers understand the real-life applications of various systems, plus how these support career advancement.
Recently, Jose has also been testing AI systems. He believes that AI is inherently unbiased—all hallucinations, inconsistencies, and security risks stem from humans.