For professionals aged 35 and above, has the job market become friendlier again?

Workers aged "35+" are being repriced by AI.

The "Insight into Job - Hunting Behaviors in the Spring Recruitment of 2026" by Maimai shows that the recruitment market has an obvious trend of "eliminating entry - level positions". Positions requiring more than 3 years of experience account for over 70%, while the number of positions for newbies with less than 1 year of experience has decreased by about 20% year - on - year.

While the number of entry - level positions is shrinking, another set of data is also worthy of attention: According to data from Zhaopin, in the spring recruitment of 2026, the number of artificial intelligence engineer positions for fresh graduates increased by 39.2% year - on - year, with an average starting salary as high as 17,038 yuan.

These two sets of data seem contradictory, but in fact, they represent the same trend. What's disappearing are traditional entry - level positions such as "writing documents and making tables", while what's increasing are ability - based positions that require decision - making skills. Even for AI engineer positions targeting fresh graduates, what's being screened for is comprehension and judgment, and the requirement for pure execution ability has been significantly reduced.

The overall demand of companies for employees has shifted from "being able to write and do" to "being able to judge and take responsibility". And those 35+ senior workers who know more about business, customers, and systems happen to meet this wave of demand.

"Ding Jiao One" talked to five people from different industries. A headhunter clearly stated that the market obviously prefers to recruit senior talents over 35 years old. An AI entrepreneur bluntly said, "We no longer recruit entry - level positions." And some 35+ workers have returned to large companies with ten - year experience and have seen this wave of opportunities more clearly.

After the conversations, everyone's feelings are quite consistent: It's a fact that entry - level positions are shrinking, but being "35+" is not a natural advantage. For 35+ people who can use AI, their experience will be significantly magnified, and the disadvantages that used to be difficult to compete with young people in terms of physical strength can be compensated for by AI to some extent. For those who can't or are unwilling to learn, experience will become a burden. The opportunity has indeed returned to this group, but on the premise that they take action themselves.

Here are their stories.

01. Entry - level Positions Reduced by 20%, 35 - year - olds Turn the Tables with Experience + AI

Blair liu | An 80s AI Headhunter in Beijing

In the past two years, the recruitment market has undergone great changes. Take entry - level positions with 1 - 3 years of work experience as an example. There are two obvious trends:

On the one hand, the demand for standardized and process - based positions in the four major fields of Internet software, finance and accounting, marketing and branding, and administrative and legal affairs has been significantly reduced. According to our company's statistics this year, the decline is close to 20%, and in some tracks, it even exceeds 30%.

On the other hand, the demand for AI - related positions such as multi - modal training, AI Agent development engineers, and network security engineers has increased by 12 times year - on - year. Take ByteDance, the company we serve, as an example. The entire AI industry chain has added more than 4,100 new positions, accounting for 50% of the total new positions. Since the beginning of last year, some clients have pre - ordered outstanding postgraduate and doctoral students through us and offered generous internship salaries. Three years ago, it was almost unheard of for campus recruits to go through headhunting channels.

The bigger change is that the market obviously prefers to recruit senior talents over 35 years old. It may sound a bit counter - intuitive, because in people's perception, 35 - year - old workers are at risk of being laid off. The essence behind this is that the requirements for people have changed.

Take the industry solution position of cloud providers as an example. In 2023, this position still accepted newbies with less than 3 years of work experience, who were responsible for basic work such as organizing documents and assisting in project implementation. This year, the position requires at least 5 years of experience in government - enterprise or manufacturing digital implementation, and the core requirements have become the ability to identify customers' business pain points, recognize the risks of large - model implementation, and take responsibility for project results.

That is to say, companies no longer rely on recruiting newbies to increase the workload, but rather improve efficiency through senior talents and AI. In the past, companies recruited to fill the execution gap. Now, they recruit to fill the ability gaps that AI cannot cover, such as decision - making, risk judgment, and complex - scenario implementation.

So, what kind of people are likely to be eliminated? From my observation, there are mainly three types: empiricists who overly rely on past paths; single - link execution veterans who repeat the same thing; and some managers.

In the past, some people had certain experience, but their core abilities still remained at the execution level. After the intervention of AI, their career space was rapidly squeezed. So, while companies prefer 35+ senior talents, another group of people in the same age group are being laid off due to the impact of AI.

At the corporate level, after the accelerated implementation of AI, the overall personnel scale has significantly shrunk. A company that used to have 1,000 employees may now be reduced to 200, and 2,000 Agents are used to complete all the work. Take my own team as an example. In the past, a project team needed 5 junior researchers and 2 consultants for resume screening. Now, with our self - developed AI recruitment Agent, only 2 consultants are left for overall planning. The manpower has been cut by 70%, but the efficiency has increased by 60%.

In the future, management positions will also shrink. Companies need not pure managers, but vertical - field experts with management abilities, who can set directions, control risks, make industry judgments, and coordinate the implementation of AI systems.

Actually, I think competitiveness is not strongly related to age. What's more important is the learning ability. Some time ago, I helped a client recruit a business leader. The candidate's professional experience was about 70 - 80% matched, but he was curious about unfamiliar fields, willing to conduct in - depth research, and able to deliver results. Eventually, he successfully got the offer from the client.

So, what we should do now is not to be anxious. We can change our mindset and run ourselves like a company: First, be proficient in using AI tools, build a personalized workflow, let AI take on 80% of the execution, and focus on 20% of the decision - making and judgment, keeping the steering wheel in our own hands; Second, break out of the single - execution link and deliberately cultivate a global mindset; Third, spend time building relationships with people. No matter how fast technology iterates, trust can only occur between people.

02. In the AI Era, Young People Solve Problems Fast, and Experienced People Pose Problems Accurately

Jin Han | A 90s Founder of an AI Startup in Zhejiang

I started my business in February this year, aiming to use AI and Agents to transform scattered information sources into intelligence products that are understandable, deliverable, and can enter the decision - making process. Since the start of the business, in more than four months, I've been recruiting. I've received more than 5,000 resumes, but only issued seven or eight offers.

This is mainly because there are not many entry - level positions in a startup, and with the advent of AI, more compound talents who are good at using AI are needed.

The reduction of entry - level positions in the entire consulting industry started last year. I used to be a partner in a consulting firm. In 2024, the company recruited four or five interns, two or three junior consultants, and also used more than a dozen PTAs (part - time assistants). But in 2025, the company basically only recruited one intern throughout the year and only used PTAs two or three times.

These people mainly helped the team with some temporary information organization, data collection, and standardized analysis. But now, AI can complete a large part of this work. And communication is also a major cost. In the past, when I led consulting consultants, I would repeatedly give feedback to newbies. They would modify their work and then show it to me. I can also give the same feedback to AI, and AI is more efficient.

So, I've found a very interesting phenomenon: The resumes I've screened out are either from fresh graduates who are good at using AI or from people over 35 years old who have experience and are willing to use AI.

Why is this the case? I think it may be because AI has magnified the advantages of these two types of people. Simply put, with the help of AI, young people solve problems fast, and experienced people pose problems accurately.

What does "solving problems fast" mean? For example, I asked an intern to use AI to create a relatively complex plug - in. A fast - learning intern may be able to complete it in two days of research.

What does "posing problems accurately" mean? It mainly lies in experience. Take myself as an example. Since I have a lot of experience in helping companies with strategic planning, I know which work processes in the investment industry can be optimized by AI, and thus can accurately describe the requirements for AI to solve. Young people, due to the lack of this experience, even if they have strong AI capabilities, may find it difficult to identify and understand the requirements, or may not know how to convert the requirements into tasks that AI can understand.

Now, AI ability has become an essential skill for every colleague. I mainly judge whether a person has truly mastered AI from three aspects: First, when did they start using AI? For example, people who started using AI in 2023 and those who only followed the trend in 2026 often have very different understandings of AI; Second, how much money did they spend? Because being willing to pay continuously shows that their work and life really depend on AI; Third, whether they have the original driving force. For example, when encountering a problem, do they instinctively think, "Let AI have a try."

Behind these appearances, we can probably see whether they have developed a muscle memory for using AI and how much bad - case experience they have. On a deeper level, we can also understand whether they know how to design the context for AI, what different models are good at, where the boundaries between models and Agents are, and where to find answers when solving problems.

Another important trait is having a low ego. I once met a fresh graduate who was good at using AI tools, but had formed a dependence on a certain work path. For example, when I asked him to complete a task of summarizing an article, a simple task like this can be directly accomplished by calling a large model, but he insisted on building a workflow. I think this idea of "sticking to one's craft" right after graduation is a big taboo in the AI era. AI technology is evolving rapidly, and everyone needs to be ready to admit that their methods are outdated and embrace new tools at any time.

At this moment, AI is rewriting the talent value ranking. The value of pure - execution and communication - only jobs is dropping rapidly, while the abilities of result judgment, understanding complex real - world scenarios, outputting credible content, self - renewal, and organizational collaboration have become more important.

However, I don't think that people over 35 naturally have an easier time finding jobs. Age is just an appearance. They may have more experience, but it doesn't mean they have mastered the core abilities of using AI well, keeping a low ego, being willing to implement, and converting experience into AI - executable tasks. Whether they are over 35 or young, if they stick to their experience and develop a path dependence, any experience may become a burden in their career.

03. Experience Really Shows Its Value in the AI Era

Old Chen | An 80s Technical Headhunter in Shenzhen

Whether a 35 - year - old can find a job is highly related to whether they can use AI.

I've been a headhunter for nearly eight years. In this year's spring recruitment, the number of entry - level positions in my hand has decreased by nearly half, especially the bottom - level technical positions for execution and writing template code. At the same time, the proportion of senior positions requiring more than 3 years, even 5 - 8 years of experience, has significantly increased. This trend will continue in the next few years after the explosion of AI tools.

Among the positions I got from large companies this year, more than 70% are related to AI. The job descriptions of these positions won't say "requiring the ability to use AI tools" because it's taken for granted. Writing it down would even seem outdated. In large - company interviews now, interviewers won't ask "Have you used AI?" They will directly ask about your previous work: What did you use AI for at that time? What was the effect? How much did the output increase? If you've just "used" it, you'll basically fail at this stage.

This change is indeed an opportunity for technical people over 35 years old. But the premise is that you have to pass the AI test first.

In the past, older programmers were disliked largely because they had relatively high costs, couldn't "endure long - hours" or "work overtime", and their output speed was slower than that of young people. But now, after AI "takes the job", what we're competing for is judgment and overall view. An experienced older programmer with the ability to manage AI can use AI to make up for the physical gap with young people. Experience really shows its value in the AI era.

Last quarter, I recommended a 42 - year - old technical director to a company. He went to the company to lead a software project and planned to release a new version. One night, he received a call from the team saying they couldn't handle it. When he rushed over, he was shocked. There was a file in the business layer and another in the data layer, each with thousands of lines of code, and the whole structure was in a mess. He asked what was going on, and they said they had just kept asking AI to modify it, and it ended up like this. They spent several hours trying to sort it out on the screen and barely got it online at dawn. Later, he analyzed this incident with me and said the problem was that no one could "manage" AI.

I also know a candidate who has been in the product field for ten years. Recently, he got an offer from a large company with almost double the salary. The reason is that he can modularize his work process and use AI to build a system, and one person can achieve the output of a whole team. The boss is willing to pay him a higher salary and save the cost of other employees. Large companies now need people who can use AI to solve problems and amplify their output with AI.

But at the same time, I'm starting to worry about those young people who have just entered the industry for two or three years. The popularization of AI tools allows them to produce seemingly "good" code at the early stage of their careers, but they have few experiences of making mistakes. In the past, a junior programmer had to go through countless debugging and rework processes. Now, AI helps them avoid these pitfalls. When they reach "35 (figuratively)", they may find that they neither have the cost and physical - strength advantages of young people nor can they handle things independently, falling between two stools.

Of course, we can't generalize about "whether people over 35 can easily find jobs". There are also some 35 - year - old candidates with good resumes, but their work methods are still very traditional, still relying on time to achieve output. Such people are also at risk in the face of AI.

People over 35 who are still looking for jobs shouldn't be discouraged. The experience you've