A career in artificial intelligence revolves around supporting the utilization of AI algorithms to mimic human intelligence, which is undeniably a rapidly expanding field. AI continues to reign over the technology industry, prompting numerous organizations to urgently seek qualified experts, sometimes even those with limited experience. Therefore, pursuing a career in AI presents immense growth opportunities.

Admittedly, AI is a highly intricate domain that demands professional expertise to forge a successful career. Nevertheless, for individuals working in the technology sector, this represents an extraordinary chance to enter the forefront of numerous emerging AI career paths. AI careers typically offer competitive salaries, often starting at six figures.

This guide delves into the potential prospects of AI careers and highlights 10 career paths that you should consider for your potential AI journey.

AI Careers: Leading Positions

The AI career positions below range from AI consultant to AI programmer to research scientist, but realize that many of these positions may overlap with one another. Indeed, the actual duties of AI careers are shifting as the AI sector itself undergoes rapid growth.

AI Consultant

The AI consultant is currently one of the most sought-after professionals when it comes to artificial intelligence jobs/careers.

AI consultants are responsible for supporting businesses and other organizations in implementing AI. Responsibilities include everything from managing implementation projects to ensuring AI solutions are compatible with an organization’s needs.

Because of these varying duties, AI consultants must understand AI in its entirety. They must understand complex topics such as machine learning and deep learning, as well as how to construct and use algorithms.

AI Prompt Specialist

Also known as prompt engineers, these specialists are tasked with developing prompts to be used with generative AI tools. Some of these tools include ChatGPT and Midjourney.

Prompts guide these AI tools and help them produce specific results. Prompt specialists must understand how these tools work and how best to communicate with them. Because of the wide use of these tools, prompt specialists can work in a wide range of industries, from advertising to manufacturing.

AI Programmer

A career as an AI programmer requires expertise in using algorithms to program AI-based services, apps and software. These programmers are also responsible for training machines to produce human-like input and for troubleshooting issues within AI-based tools.

Programmers must have a solid handle on programming languages such as Python and Java. They must also understand the basics of software development and know the ins and outs of AI concepts.

AI Developer

While similar to programmers, an AI developer instead develops and designs the AI-based services, apps and software organizations use. For example, AI developers ensure that the user interface of an AI-based tool is easy to use.

AI developers also test software applications to ensure they result in the desired outcomes. In some cases, AI programmers and developers will work alongside one another.

Developers must have solid problem-solving skills and creativity, while also understanding data engineering and analytics. This AI career tends to be highly lucrative.

Data Scientist

A data scientist’s key responsibility is solving complex problems using data. Data scientists perform a wide range of duties, including building models using programming languages, finding patterns in data sets, communicating insights to stakeholders and consulting with organizations on how to best use their data.

Data science plays a key role in AI. Scientists work to build the algorithms necessary to uncover patterns. Those patterns can then be used to train AI models.

Research Scientist

As AI continues to evolve, organizations will need to find innovative ways to use it. An AI career as a research scientists involves researching the use of AI to uncover new opportunities. They also build algorithms and perform experiments to test new AI methods.

Research scientists must be inquisitive and creative. They must also have a firm grasp on complex subjects such as statistics, data analytics, machine learning and natural language processing.

Machine Learning Engineer

The machine learning engineer plays a critical role in the development of AI programs, applications and software. Machine learning engineers work to design the models and algorithms that make AI work.

The process of designing these models requires the engineer to organize data, test models, program models using languages like Python and other responsibilities.

Deep Learning Engineer

Deep learning is a branch of machine learning. However, deep learning goes beyond machine learning in that it enables AI models to learn and make their own decisions. In other words, it enables machines to learn and act in the same way the human brain does.

Deep learning engineers use this process to build highly intelligent AI models, most often for the purpose of predictive analytics. These engineers must be experts in machine learning, neural networking, data science and programming.

NLP Engineer

NLP stands for natural language processing, which refers to a computer’s ability to understand human language. NLP is one force behind popular AI tools such as chatbots like ChatGPT.

A career as an NLP engineers requires deep expertise programming AI models and systems that can understand human language. This means that while NLP engineers must understand programming and AI, they must also be experts in language and linguistics.

Robotics Engineer

Robotics engineers are tasked with using machines and algorithms to build robots. They’re also responsible for testing and maintaining robotic machines across a wide range of industries, from manufacturing to retail.

The skills required to be a robotics engineer are a unique mix. Not only do you need to understand AI, programming, and mathematics, but you must also have mechanical skills.