For years, software developers on H-1B visas benefited from steady demand among US technology employers. That market is becoming more selective as companies redirect spending toward AI and rely more heavily on coding assistants.

Recent layoffs at companies including Meta and Amazon have added to the uncertainty, with engineering and software roles affected even as major technology companies continue to deepen investments in AI.

Developers and analysts say traditional engineering roles are becoming harder to land, recruiters are asking more often for AI-related experience, and workers are being pushed to keep pace with tools such as GitHub Copilot, Claude, and ChatGPT.

The shift is being driven by both AI investment and broader economic uncertainty, according to Pareekh Jain, CEO of Pareekh Consulting. Companies are changing the profile of the developers they want, hiring fewer people in some areas while paying more for AI talent.

“AI investments are changing company hiring strategy,” Jain said. “They require a different profile, fewer numbers, and also across geographies.”

This shift is colliding with a tougher sponsorship environment for H-1B developers.

Jain said companies are more selective about hiring visa-dependent workers than they were two or three years ago, especially when permanent residents and US citizens are more available in the market.

“Companies are not looking for H-1B now,” Jain said. “They are building a local workforce and preferring green card holders and citizens.”

Employers may now be more likely to consider H-1B candidates only when they have immediate project needs, rather than building a longer-term bench of visa-dependent workers.

Concerns are visible in public forums used by technology workers. In one January post on Blind, an anonymous senior software engineer with seven years of experience said she had been laid off while on an H-1B visa and was “not interview-ready,” highlighting how quickly job loss can become a visa problem for H-1B workers in the US.

Junior developers face the squeeze

The combination of AI tools and tighter hiring is hitting early-career developers hardest, said Adarsh ML, a product engineer at Ather Energy who tracks global engineering hiring trends.

“Companies are increasingly looking for specialized engineers with machine learning and data science skills,” Adarsh said. “Job opportunities for people with zero to three or four years of experience are not really there anymore.”

The shift is also changing team structures, Adarsh said. Earlier, one manager may have had two or three interns and several freshers reporting to them. Now, many of those roles are being replaced by AI agents.

“Companies now want people who understand software well enough to catch the mistakes these AI agents make,” Adarsh said.

That creates a longer-term risk for the software talent pipeline.

“If companies only want people with five years of experience to manage AI agents today, who will have that experience five years from now?” he said. “There may not be enough experienced developers left.”

AI literacy becomes baseline

The impact is not the same for every role. Sophia James, an Indian software professional based in the US who works in database monitoring, said AI has not significantly changed her team’s daily workflow. But AI literacy is becoming a management expectation.

“Managers are trying to understand whether we are keeping up with the changes happening in the market,” James said. “Recently graduated students, whether BS or MS, are finding it difficult to get jobs. But people who already have jobs, like us, are not facing that much of an issue in terms of projects continuing.”

Jain also stressed that AI literacy is now becoming a baseline expectation for software developers, even outside AI-focused roles.

“Being AI-literate is a must now, even if the role is not directly in AI development,” he said. “This is like knowing Excel even if you are not from finance in the earlier era.”

Fewer developers required

Jain said AI coding tools are likely to reduce the number of developers companies need for similar tasks, making the technology deflationary for some software work.  

But Jain added the impact may not be entirely negative. Enterprises will need to invest in data, cloud, and modernization to become AI-ready, creating new work. AI could also encourage companies to build more applications internally instead of buying from SaaS providers, potentially creating opportunities for IT services firms.

The effect is already visible in hiring decisions. Nikhil Dhiman, head of engineering at CarInfo, said AI is changing the economics of early-stage software development, particularly when companies are building proofs of concept or testing new ideas.

“Some companies are very cautious now,” he said. “They want to leverage AI more and hire less. They just want to see the impact first.”

Navigating the new hiring market

Familiarity with tools such as ChatGPT and GitHub Copilot is now a baseline requirement for developers, said Sanchit Vir Gogia, chief analyst at Greyhound Research.

Developers need deeper expertise in areas such as cloud infrastructure and data engineering, as well as security and AI governance, he said. Those skills are closer to the systems enterprises need to validate and scale, rather than the routine coding work AI tools are starting to compress.

“The engineer who only produces output grows easier to replace as the output grows easier to generate,” Gogia said. “The engineer who can validate it, secure it, situate it in a real business, and stand behind the result becomes harder to replace.” For H-1B developers, he said, adaptation also requires visa planning. Developers should understand portability rules and employer sponsorship timelines before a job loss forces urgent decisions.

“A high-skilled worker has up to 60 days after a role ends, and the right to begin new employment the moment a valid portability petition is filed,” Gogia added. “The strategic error is treating that window as a safety net rather than a planning horizon.”

The article originally appeared on InfoWorld.

Tech companies seem to be falling over each other these days in firing people to either replace them with AI or to pay to build AI infrastructure. Wouldn’t it be nice if they at least waited until AI actually worked for business?

On the one hand, top tech businesses such as Amazon, Block, Cisco, Cloudflare, and Meta have all announced that they’re slashing payrolls — either because AI can do the same work as people or they need the cash to build out their AI infrastructure. Isn’t that great? All together, of the 37,638 tech job cuts so far this year, 47.9% — almost half —  can be tracked back to AI. 

On the other hand, despite all the AI hype and hysteria, no one has yet proven that AI is, generally speaking, really all that helpful for businesses. Oh, I know, I know. You did great things with OpenClaw vibe programming. Microsoft’s CEO, Satya Nadella, claims 20% to 30% of the company’s code was written by AI. And Nvidia assures us that 88% of its surveyed customers report AI has increased their revenues. 

But really, what else would they say? “Dear Board, we just blew half a billion bucks on Nvidia GPUs, and we’re losing money hand over fist?” I don’t think so.

The truth is, as an IDC study reports, a mind-boggling 88% of proof-of-concept AI projects never reach production. Lest we forget, MIT’s The GenAI Divide: State of AI in Business 2025 study found that 95% of AI projects fail to deliver measurable P&L impact. 

Now, I have to acknowledge that AI is finally becoming truly helpful in business. As a guy who knows a thing or two about programming, Linus Torvalds, creator of Linux and Git, said at Open Source Summit North America, “I’m personally 100% convinced that AI is changing programming.” He estimates that “AI will increase your productivity by a factor of 10.” 

But is that reason enough to slash make workforce cuts of between 10% to 40%? (Short answer: No. Longer answer: Noooo!)

It’s not just the mass firings. Workers who are either awaiting the axe, or have escaped it for the moment, are miserable. As one Meta employee told The San Francisco Standard, “I tend to cry in the shower,” and, “A lot of my feelings about my job are about the general chaos and not just the layoffs. ” 

So, explain this to me: When everyone knows AI-driven layoffs are coming, exactly how well do you expect them to work? You really think they can give their best? 

Making matters worse, it’s an open secret that IBM, Google, and Meta are having their employees train their AI replacements. As a popular meme puts it, workers are now “building your own coffin.” Is it any wonder that a lot of people — 29% of all employees and 44% among Gen Z workers —  are deliberately sabotaging work when the boss insists they train their AI replacements?

It also sure doesn’t help office morale when the CEO keeps saying AI will replace half of all employees. A particularly egregious example of this was when Standard Chartered CEO Bill Winters proclaimed his bank would slash thousands of jobs and replace “lower-value human capital” with AI.  

He’s since backed off the claim, but come on — we all know he meant it. Just like all the other CEOs who’ve said similar things, between FOMO and the knowledge that AI job news is sure to make the stock price jump, they’re eager to cut headcounts and boast about how successful AI will make them. 

What happens a few quarters down the road? Their attitude today seems to be let  tomorrow take care of tomorrow. I hate to tell them, but that really doesn’t work in the long run. (Not, mind you, that a future much farther ahead than the next quarter seems to matter much anymore to business executives.)

It should. As a recent Deloitte study stated: “Most respondents reported achieving satisfactory ROI on a typical AI use case within two to four years. This is significantly longer than the typical payback period of 7seven to 12 months expected for technology investments. Only 6% reported payback in under a year, and even among the most successful projects, just 13% saw returns within 12 months.” 

AI, in short, is not the miracle cure for what ails businesses that its fans claim. 

Will that stop businesses? I doubt it. While I appreciate that California Gov., Gavin Newsom is trying to bandage the AI job bleedout by mandating studies on subsidizing companies to keep employees rather than replace them with AI, I doubt that will do much to staunch the wound. 

At the Open Source Summit North America, Linux Foundation CEO Jim Zemlin was optimistic about AI and jobs. He pointed out that, thanks to AI becoming  “pretty damn good coders,” the number of open-source projects on GitHub has led to a “surge of new code and projects.” 

Zemlin also believes that while few developers will write code, “engineers will still design, review, secure, and integrate that code.” (He’s referring to what’s becoming  known as forward-deployed engineers.) This, in turn, will supposedly lead to tech job growth. 

I’d feel a lot better about that prediction if I believed the C-suite suits at most companies were capable of truly forward-looking thinking rather than focusing entirely on hiking the stock price by making the next quarter look good through staffing cuts. 

In the long run, sure, AI will make us more productive. But, we’re not there yet. For now, companies need to keep employees happy, not shove AI down their throats — and work out carefully and thoughtfully how AI will really work for business.