Engineers Spend Days Fixing AI Code Created in Hours

Low-code and no-code platforms were supposed to reduce the need for software engineers. Instead, they are unexpectedly creating more demand for senior engineers—and pushing their salaries higher.

AI-powered platforms can now churn out massive amounts of code within hours. But experienced programmers are increasingly required to double-check their work. Artificial intelligence does not actually understand the unique rules and requirements of a specific business. As a result, it can produce code that looks fine at first glance while quietly skipping crucial safety checks and security measures.

“I’ve seen this pattern firsthand: AI and low-code tools don’t reduce the need for engineering judgment; they raise the cost of not having it,” said Master Joe Phillips, a Costa Rican technology entrepreneur whose company, Trifecta Software, developed custom applications for several United States clients.

Phillips warned that using these fast, automated tools without an expert guiding the project can lead to mistakes that are much bigger and far more expensive to fix later.

“My team gets hired all the time to completely redo this job,” he said.

Recent studies support Phillips’s statements. Research by CodeRabbit found that AI-written code contains 1.7 times more issues overall compared with code written by humans. Logic and correctness errors are 75% more common, while security vulnerabilities are up to 2.74 times higher.

“AI can finish work in one day, but it still takes a week for design, architecture, and end-to-end testing of code before it makes it to production,” says Mayank Choubey, a Bay Area-based software engineer who works for AI software firm Ushur.

The problem, he said, is the sheer volume of code AI generates every day, which can break things without anyone noticing. His team therefore spends far more time building a robust testing framework, adding test cases, and running them with every code check-in.

What is clear, however, is that AI coding tools have reduced the need for junior engineers.

“In U.S. nearshore specifically, clients are asking for fewer junior coders and more senior engineers who can supervise AI output; this has actually pushed hourly rates up for experienced talent,” Phillips added.

“When a junior developer’s day was billed at a blended rate, nobody separately priced ‘who is checking this generated code. Now that AI writes the code in seconds, someone has to consciously decide to pay for that checking function,” said Roman Marszalek, CEO of Dr Logic Limited, a managed services provider based in London.

The shift is changing not only who companies hire, but also how much they are willing to pay for experienced talent.

Skyrocketing Salaries for Seniors

An April 2026 analysis by Business Insider of more than 5,800 work-visa applications filed by Meta in 2025 found that base salaries for software engineers reached as high as $450,000.

Base pay is only part of the compensation package for many senior roles. Companies are also offering company stock through equity grants and cash bonuses. For some senior engineers, these stock awards now regularly add 20% to 100% on top of their base salary. Nearly 40% of senior job offers also include sign-on bonuses ranging from $5,000 to $25,000, as companies compete to attract talent from rivals.

“Senior engineers and architects who can make good technical decisions, challenge bad assumptions, and understand the consequences of those decisions across an entire system are becoming more important,” said Kacper Gazda, CEO of Milo Solutions, a Polish software development firm.

The pay gap is most pronounced in roles focused on Artificial Intelligence and Machine Learning (AI/ML). A 2026 analysis by NASSCOM, an Indian technology lobby group, showed that while junior AI roles start around $7,000 to $14,000, senior AI/ML engineers command a 25% to 40% market premium over generalist software engineers, pushing senior total compensation to between $65,000 and $180,000 in that market.

In the United States, senior AI and machine learning engineers routinely command $250,000 to $400,000—30% to 50% more than standard backend developers who focus on the behind-the-scenes server infrastructure.