TrueUp is tracking over 67,000 open software engineering roles globally, the highest in more than three years. The headline is correct. What the number does not tell you is what those jobs actually require now.
TrueUp's hiring data shows over 67,000 open software engineering positions globally, the highest it has been in more than three years. The engineers struggling to fill them are the ones still waiting for the job to go back to what it was in 2022.
The "AI is going to kill all the developer jobs" narrative has officially been measured, and the data does not support that claim.
TrueUp, a hiring analytics firm that tracks real-time tech job postings, is currently tracking over 67,000 open software engineering roles globally. That is a 30% increase since the start of 2026 and roughly double the number of openings from the market low in mid-2023. TrueUp founder Amit Taylor has been direct about it: the data does not support the claim that AI is replacing engineers.
So the fear was wrong. The jobs are there.
Here is what those jobs actually look like now.
Companies are not posting 67,000 openings to rebuild the engineering teams they had in 2022. They are hiring for a different kind of engineer than they were then.
The shift is visible in how teams have been restructured. Organizations that went through layoffs in 2023 and 2024 did not simply rebuild the same teams when the market turned. They rebuilt leaner, with fewer people expected to do more. The engineers getting hired are the ones who can operate with the leverage that AI tools provide and actually know that they are doing it.
That changes the job description in ways the hiring number alone does not capture.
The other thing the TrueUp data should push us to think about is what happens to all the code that is being written at this pace.
When AI tools can generate entire features in a fraction of the time it used to take, the output rate goes up dramatically. Someone still has to own what gets shipped.
Amazon learned this in a very visible way. An AI-assisted deployment caused an outage because the review layer that would normally catch the issue was not built to handle the speed at which AI was generating and pushing code. The AI moved faster than the human oversight could keep up with.
That kind of incident does not happen because AI is careless. It happens because the engineering culture around it had not adapted yet.
More open positions means more surface area. More AI-generated code means more places where an engineer needs to understand and own what was built, even if they did not personally write it. The responsibility did not transfer to the AI when it wrote the code. It stayed exactly where it has always been.
The roles being filled are not going to engineers who grab a ticket, implement it to spec, and open a pull request. That workflow still exists. There is significantly less value in being the person whose entire skillset lives there, because AI tools can compress that loop dramatically on their own.
The engineers getting hired are the ones who can:
These are not entirely new skills. Experienced engineers have always known that the best developers think about the product and the system, not just the ticket. What changed is that these skills are now table stakes instead of differentiators.
There is a version of this conversation that sounds like: engineers with a decade of experience are suddenly being undervalued.
That is not quite right.
The roles that are harder to find are the ones where the primary value was task completion at the atomic level. Writing boilerplate. Translating a requirement into a function without needing to deeply understand that requirement. Being the person in the room who knows a specific framework well enough to implement things quickly.
AI handles that tier faster and without complaint. The engineers who built their entire identity around that kind of output speed are navigating the hardest market.
The engineers who always understood the full picture, who pushed back on tickets that did not make sense, who could hold the system architecture in their head while also writing the code, those engineers are more valuable now.
The 67,000 number is real. The job market for software engineers is genuinely strong. AI did not eliminate the profession.
It did, however, raise the floor.
The question for any engineer right now is not complicated: are you building the skills that make AI more effective, or are you spending energy trying to compete with it on the things it simply does better?
Understanding what you are building and why, owning the code that gets shipped regardless of who wrote it, and knowing how to orchestrate a collection of AI tools toward a real outcome. That is the job now.
The openings are there for the engineers doing that work.