AI jobs: how to find one, and how much can you earn – interview

Since the release of ChatGPT, there have been ongoing reports and concerns that AI might make many jobs redundant. While some of these concerns are well-founded, there is also another side of the coin – AI is creating a lot of new career opportunities.

What are the most sought-after positions created by AI? What skills does one need to land a job in the field, and how much could one expect to earn? We talked to Sriram Ramakrishnan, Senior Vice President of Experis, a Manpower Group company that specializes in IT staffing services, to find out. We also asked his opinion about tech layoffs.

It’s important to market yourself

Ramakrishnan groups the most in-demand AI jobs into several categories. The current hottest specialty in the market is language model expertise – people who work on machine learning and other AI-based algorithms. Generative AI engineers represent another widely sought-after role. The expert explains that these are specialists who are very specific to certain industries and segments.

"There is also a heightened need for migration specialists – once you have the data, you have to load all this data into an AI engine. It requires certain skills and nomenclature to load them. AI ops and ML ops are other skill sets that are in demand the most."

However, finding a job in such a position may require solid technical skills, experience, and knowledge. It’s also possible to find an entry-level job being skilled in administrative functions and become "an expert user of AI, as opposed to creating AI models."

According to Ramakrishnan, it may take two to four months to gain a grasp of AI. The first two months are more about understanding and playing around with technology. Following that, people delve into learning about the data ingested into an AI engine and the process of training it.

The good news is that there is a lot of material to learn from. Resources are offered by top AI engines, universities, educational platforms like Udemy, and companies. Ramakrishnan says that companies offer academy courses at a very negligible cost, which could be only around $2,000.

However, knowledge does not guarantee a successful job hunt.

"Merely applying for a job on LinkedIn isn't likely to be helpful because there are so many applications. It's important for an individual to actively engage in local communities, participate in outreach events, and publish their code and use cases. So, it comes with self-marketing. Additionally, registering with various agencies may also prove beneficial," Ramakrishnan said.

AI skills vs traditional IT skills – how do they differ?

Some skills required in the field of AI may overlap with those needed in traditional IT jobs. However, there are a few key differences. According to Ramakrishnan, traditional IT jobs span multiple technologies and are specific to certain skills. For example, database (DB) experts focus on DB skills, front-end engineers focus on the user interface (UI), and Java developers focus on Java technologies.

Meanwhile, AI jobs require a good understanding of an organization’s data.

The primary skills that are required for AI jobs are knowledge of data, including modeling, mining, warehousing, migration, and programming – apart from traditional programming languages, one is required to have experience with scripts like Python and R.

According to Ramakrishnan, one must also know language models and have lightweight user interface skills. A great value addition would be exposure to AI technologies like Gemini, Vicuna, Claude 2, and others.

"An AI engineer is expected to have well-rounded skills covering the areas mentioned above. Hence, AI skills are in such demand in the marketplace now," Ramakrishnan explains.

However, exact skills vary and depend on certain positions. For example, research analysis requires fundamental AI skills like basic natural language processing, statistical knowledge, and exposure to scripting languages like Python.

Mid-level prompt engineers require language model skills, algorithms, API, NLP, Python, and hands-on AI tool skills like Gemini and GPT (See the table below).

How much can one expect to earn?

Salaries in various AI roles can vary from around $70,000 to $140,000 in a year in the US, depending on the specific position and experience, reads the data provided to Cybernews by Experis.

For example, a Junior AI engineer can expect to earn around $80,000 a year, a prompt engineer around $90,000, while an AI engineer with a prompt engineer at least five years of experience may earn around $120,000 and $140,000, respectively.

The salary range in AI-related jobs is quite similar to that of traditional AI jobs (see the table).

According to Ramakrishnan, some positions, such as software engineers, may earn a bit less with the introduction of AI since some of the higher-level positions are shunted when people climb up the ladder to new roles. This is because AI allows a lot of meaningful data-driven work.

However, if a person is skilled in AI, his salary and demand only increases. The expert says that implementing AI tools is also important for other traditional IT specialists, including developers.

“I think it's mandatory for them to pick up this AI model and ML model as part of their development algorithm to bring in efficiency. If they don't do it in six months, these roles might also become redundant because, with the introduction of AI, your traditional say, two months of work can be accomplished in 15 days.”

One domain where we will see an increase in jobs because of AI is cybersecurity. This is because businesses expose more and more sensitive data to the AI world, potentially leading to more vulnerabilities and hacks, Ramakrishnan explains.

Layoffs may slow in Q4

The surge in AI technology is also one of the reasons why big companies are cautious with their spending. This year alone, over 200 companies laid off around 60,000 employees. In April, 20,000 employees were let go from companies including Apple, Google, and Amazon.

According to the expert, because of the surge in AI, firms are investing their capital cost in determining key use cases, which enables them to grow, cut costs, and try to utilize their employees for value-added work.

Another reason companies are cautious in their spending is the talent gap. The expert elaborates that when technology like AI evolves, firms find it difficult to reskill their current employees. A huge effort is going into upskilling and reskilling employees where it makes sense.

Then there is the impact of post-pandemic effect and high inflation.

"Firms hired more resources than needed during pre- and post-pandemic, especially when they had the luxury of having resources work globally in a remote manner. Federal rates range from 5.2 to 5.5%. This also puts cost pressure since investors are going away from tech sectors for a safer, higher return; This directly impacts firms in making tough decisions."

However, Ramakrishnan says that amidst layoffs, we are also seeing strong employment environments and steady job orders. He forecasts that tech layoffs may continue in Q3, but we can probably see layoffs slowing towards Q4 as they prepare for 2025.