As much as we would not like to agree, AI is here to stay, and it will continue to influence our digital world. From the way we write to the way we work; AI is changing everything. So, if you’re looking for a way to join the growing AI industry, you’re not too late.
In this article, we will break down two roles in AI that seem similar but are actually quite different: the AI Prompt Engineer and the NLP (Natural Language Processing) Engineer.
Both careers involve working with language and artificial intelligence, but they require different skills, responsibilities, and learning paths.
An AI Prompt Engineer is someone who specialises in writing precise inputs, known as prompts, for large language models (LLMs) like OpenAI’s ChatGPT, Google’s Gemini, or Anthropic’s Claude. Their main goal is to get the AI to respond in a certain way, whether that means generating content, solving a problem, or answering questions early.
Prompt Engineers do not build AI itself; they help write the instructions that guide the AI’s output. They experiment with tones, structure, keywords, and formatting to get the best results from these systems.
To become a prompt engineer, you need to have strong writing and communication skills. You have to be someone who thinks critically, understands how language models behave, and has basic knowledge of AI tools and platforms.
You might find this role easy if you are a writer, educator, creative, marketer, or any woman who is looking for an accessible way to work in AI. It is also a good fit for product managers and UX designers who already know how to think about user experience and behaviour.
Now that we know about prompt engineering, what is NLP engineering?
NLP stands for Natural Language Processing, a branch of artificial intelligence that focuses on how computers understand, interpret and generate human language.
An NLP engineer is a technical expert who builds the models and systems that allow machines to understand and process language. They work on tasks like speech recognition, machine translation, text summarisation, sentiment analysis, and more.
Unlike prompt engineers, NLP engineers are involved in writing code, training models, and handling large datasets.
For you to be a NLP engineer, you need to have advanced programming skills, know about machine learning and deep learning frameworks like PyTorch, have a good knowledge of data science and statistics, have experience working with large language models and NLP libraries and also have a formal training in computer science, linguistics or mathematics.
This is a good career path for people who have a strong technical background, especially those who enjoy problem-solving, math, and programming. It is important to note that this role is currently in high demand.
While both roles are part of the AI industry and involve working with language, their focus is very different.
- Prompt Engineers talk to the AI and write instructions to guide its behaviour.
- NLP Engineers build the models that make the AI understand and process language.
If you are someone who loves language, creativity, and experimenting with how machines respond to you, prompt engineering might be the best fit for you. This is relatively new and more open to people transitioning into tech.
However, if you prefer coding, research, and solving technical problems, NLP engineering is your path. It is more established, with clear career tracks and opportunities in big tech, research labs, and startups.
So, if you’re interested in working with AI, take some time to research each role, decide which one aligns with your strengths, and start learning.
Leave a Reply