Tech Hiring in 2026: The Rise of the Specialist

I once worked with a boss who would refer to hiring job candidates as “getting married.” Are we ready to marry this candidate? Is that one a bad match? Yes, it’s not exactly language to make an HR manager swoon, but the framework makes sense: Hiring means a long-term partnership where, ideally, both parties can benefit and grow together. But in 2025, suitors were dragging their feet — except when it comes to AI-related roles. Earlier this decade, companies love-bombed developers and engineers, and put a ring on it very quickly —  in many cases, too quickly. The Great Resignation of 2021-22 found technologists jumping ship en masse and trading their skills for big pay raises. Then, late in 2022, the Age of AI began in earnest, with the release of OpenAI’s ChatGPT-3, followed by new commercial large language models from Anthropic, Google, Meta and more. Mass layoffs, often shedding workers who were picked up during the Great Resignation, followed. As we pass from 2025 into 2026, the AI ecosystem grows by the day. Suddenly, everyone needs AI expertise. Suddenly, no one’s hiring junior devs. Suddenly, everyone’s building AI agents to automate tasks large and small. Economic, technological and geopolitical uncertainty muted the sound of wedding bells. Employers, wary of taking on more workers until the dust settles, grew evasive when pressed for a commitment. Welcome to “the Great Hesitation,” a term credited to George Denlinger, operational president of U.S. technology talent solutions at Robert Half, in a Wall Street Journal article from last May. I heard the term again in October, in a keynote address at All Things Open in Raleigh, N.C., delivered by Taylor Desseyn, a veteran tech recruiter and vice president of global community at Torc, a talent platform. AI, Desseyn said in his keynote, doesn’t deserve all the blame for the hiring managers’ skittishness. “We’re dealing with the over-hiring in 2022 and I truly believe AI has a marketing problem,” he said. “The reason why people are getting laid off is not because of AI. We as human beings like to blame things … the blame should be for the over-highering than happened in 2022.” The Unmistakable Demand for AI Skills But there’s no denying one obvious takeaway for the new year: If you have experience in AI or machine learning, the 2026 job market looks bright. A little more than half — 53% — of U.S. tech job postings in November required AI/ML skills, according to Dice’s 2025 Tech Jobs Report, released in December. That’s up from 48% of October job listings; in November 2024, that figure was 29%. !function(e,n,i,s){var d="InfogramEmbeds";var o=e.getElementsByTagName(n)[0];if(window[d]&&window[d].initialized)window[d].process&&window[d].process();else if(!e.getElementById(i)){var r=e.createElement(n);r.async=1,r.id=i,r.src=s,o.parentNode.insertBefore(r,o)}}(document,"script","infogram-async","https://e.infogram.com/js/dist/embed-loader-min.js"); Source: Dice December 2025 Jobs Report. And most organizations plan to increase their investment in AI in 2026 – 84% of respondents to a survey by CompTIA said they plan to at least moderately increase resources for AI in the New Year, The IT outlook report survyed included more than 1,000 business and technology professionals. For other roles, however, the news is less sunny. The CompTIA outlook report saw optimism anong its respondents but still laced with caution. Seventy-seven percent of survey participants said they feel good about their company’s fate in 2026, but only just over half said they expect to exceed 2025’s revenue or profitability. The Dice report saw an overall decline in U.S. tech jobs listings this past November, down 15% from the previous month and down 10% from November 2024. Another hiring benchmark, CompTIA’s December report, also found tech job postings overall were down in November compared to the previous month – though up slightly compared to November 2024. That CompTIA report also found that 41% of current tech job listings required some level of AI skills. What Skills Are in Demand for the 2026 Job Market? So what skills does someone need to position themselves for a job market where AI is the main character? The Dice report lists the skills that are growing fastest in popularity in tech job listings, year over year and from October to November. !function(e,n,i,s){var d="InfogramEmbeds";var o=e.getElementsByTagName(n)[0];if(window[d]&&window[d].initialized)window[d].process&&window[d].process();else if(!e.getElementById(i)){var r=e.createElement(n);r.async=1,r.id=i,r.src=s,o.parentNode.insertBefore(r,o)}}(document,"script","infogram-async","https://e.infogram.com/js/dist/embed-loader-min.js"); Source: Dice December 2025 Jobs Report. !function(e,n,i,s){var d="InfogramEmbeds";var o=e.getElementsByTagName(n)[0];if(window[d]&&window[d].initialized)window[d].process&&window[d].process();else if(!e.getElementById(i)){var r=e.createElement(n);r.async=1,r.id=i,r.src=s,o.parentNode.insertBefore(r,o)}}(document,"script","infogram-async","https://e.infogram.com/js/dist/embed-loader-min.js"); Source: Dice December 2025 Jobs Report. The second most frequently advertised role in November, after software engineer, was data engineer, with data scientist the fifth most commonly sought, according to the Dice report. There’s a huge shortage of qualified people for those roles, according to Carrol Chang, CEO of Andela. “A lot of companies want to get started with AI, but in order to do that, your data has to be clean, and it has to be prepared to be pumped into the models,” Chang told The New Stack. “And so that means that the work of data engineers, machine learning engineers, data scientists, data analysts, these are job categories that are in high demand now and are probably only gonna grow.” In 2026, according to a McKinsey Global Institute projection she cited, the candidate pool for data scientist roles will comprise only about half the expected demand. The Forward Deployed Engineer: The ‘Hottest Job in Tech’ Inclusive of AI but broader, the “forward deployed engineer,” or FDE, is “probably the hottest job in tech right now,” according to Chang. She echoed a similar claim made by Joe Schmidt IV, a partner at Andressen Horowitz (a16z), in a June whitepaper for the venture capital firm. AI startups, he wrote, need to provide customers with help implementing their products: “Enterprises buying AI are like your grandma getting an iPhone: they want to use it, but they need you to set it up.” The FDE role, pioneered and named by Palantir, means an engineer who switches between being embedded in teams that directly serve customers and engineering teams that build products. At Andela, Chang said, “We like to tell clients, you need FDEs, not FTEs.” To make a foundation model trained in a research lab work accurately in production, she said, the skills of a forward-deployed engineer are crucial. “Let’s say you are a large health insurance company, and that means that you have to process tons and tons of claims data every day,” Chang said. “The accuracy in the way you process it is obviously very important. There are lives on the line, there are financial livelihoods on the line. “If you were to deploy these foundation models from the labs out of the box, you’d probably get about 60% accuracy. That’s obviously not good enough. Everybody knows that’s not good enough. So then what do you do? Well, in order to improve the accuracy of that model, you have to train it on your own data,” a process fraught with potential data security risks. To get the job done, she added, “You need a forward-deployed engineer. These are the engineers that understand the models very fluently, and then they also understand enterprise data, they understand how to do fine-tuning, how to create reinforcement learning loops, and ultimately get the enterprise to the level of accuracy it wants.” Why Specialists and Production-Ready Skills Are Crucial Overall, a big difference between hiring during the Great Resignation and now appears to be a greater emphasis on specialists over generalists. In a separate presentation he gave on career development at All Things Open, Desseyn advised a packed room of attendees, “I would say be very specific right now. And honestly, I think we’re in that trend for a while.” As with any new industry, the AI movement, like Kubernetes and cloud before it, offers opportunities for early adopters. “There’s a huge opportunity to be a subject matter expert in an industry on how to implement AI service,” Desseyn said. The consultant space in particular, he said, is likely to see a boost: “The next evolution is, hey, we want to hire this consultant to come in to help us with AI processes and things to implement in this industry.’” For those who want to pivot into other parts of IT — data engineering, FDE, sales engineer roles, etc., a little bit of initiative, of volunteering for stretch assignments and side quests, goes a long way, Desseyn told the All Things Open crowd. “Right now, we are in the climate of doing the job before you can get the job, whether you like it or not,” he said. It’s not just about knowing how to play with the AI toys, Chang said. For both candidates and hiring managers, “the most important advice I would give is to focus on production-ready practice. So, for candidates, what that means is don’t just learn how to use GitHub Copilot, Cursor and Windsurf, but actually do projects that give you real-world, on-the-job skills.” For the job seeker, “you want to prove, in an interview, that you don’t just know the theory, and you don’t just know how to play around with the tools, but you have actually built projects that are production-ready. You need to focus your skill development and your practice on that. On the flip side, for hiring managers, that’s what you should be looking for in candidates. “You should be asking questions and designing your assessments around production-ready work, and you...