Following the IT and tech hiring boom during the Covid-19 pandemic, companies made space for AI initiatives that resulted in increased layoffs. But new data reveals that some IT hiring trends are starting to turn around.
Pay in the most AI-exposed occupations grew around 46% since 2021, compared to only 25% for jobs in the least-exposed category, according to the Dice Tech Sentiment report. The data reveals this gap began to grow in 2024 and continues to grow as job pos
Following the IT and tech hiring boom during the Covid-19 pandemic, companies made space for AI initiatives that resulted in increased layoffs. But new data reveals that some IT hiring trends are starting to turn around.
Pay in the most AI-exposed occupations grew around 46% since 2021, compared to only 25% for jobs in the least-exposed category, according to the Dice Tech Sentiment report. The data reveals this gap began to grow in 2024 and continues to grow as job postings rebound after several rough hiring years.
As organizations begin to realize AI initiatives and investments, they’re now looking to fill their ranks with specialized skillsets, and it’s driving increased compensation. AI has changed the skills businesses need, and 84% of executives report they currently struggle to find specialized local talent while 64% say they feel unprepared for ongoing disruption, according to data from a 2026 report from Globalization Partners.
In a few short years, AI has caused multiple swings in tech hiring. As organizations understand the skills they need to realize AI visions, hiring, for now, appears to be on the upswing for candidates and jobseekers, with more competitive offers. On the employee side, as AI transforms job roles and business functions across every industry, there are, however, increased reports of burnout and a widening gender gap.
Salary boost for specialized skills
AI is currently creating some of the fastest growing and highest paying opportunities in today’s labor market, according to LinkedIn Research. Data reveals that AI job postings have doubled in 2026 from 2023, with the average job listing around $177k in compensation for AI roles, compared to $80k for non-AI roles.
Salary offers and benefit packages have again become more competitive, with 72% of employers saying they’re increasing compensation budgets to attract and retain top talent. Additionally, 65% of tech leaders said they’re offering salaries above their planned range, with 87% stating the top reason being a need to secure candidates with specialized skills, according to Robert Half.
Tech leaders are also seeking specific skills, with 92% acknowledging internal plans to offer higher pay for relevant AI skills. Across every industry, 42% of all business leaders say they’ll pay more for AI-related experience compared to other general tech skills.
Additionally, pay transparency, once relatively taboo in the hiring process, has now become normalized in hiring with 96% of organizations reporting they either already share compensation or plan to soon. Sharing compensation on job postings has several benefits including improving the quality of the candidate pool, more efficient salary negotiation, and a reduced time to hire. Business leaders seem to recognize the benefits, with 67% of employers saying their company takes pay transparency beyond legal requirements, offering more information than is legally required, adds Robert Half.
AI accelerates employee burnout
As daily AI use quadrupled over the past year, burnout doubled and confidence in tech’s long-term future dropped from 80 to 60%, according to Dice. The data reveals around 74% of employees say they plan to change employers in the next year, and 55% say they’re actively job searching, despite only 41% saying they believe they’ll find a better position.
Dice also reveals nearly half of all employed tech professionals report feeling burnout, with around 25% describing themselves as very burned out. And among those reporting burnout, tech and AI professionals express the highest rates.
High levels of burnout can cost companies lost productivity and hurt bottom lines. In 2025, a staggering 10 trillion was estimated to have been lost globally due to disengaged and burnt out employees, according to Globalization Parters. If companies are losing profits through employee burnout, costs of AI investments need to be greater priorities when planning AI initiatives.
AI is meant to boost productivity and efficiency, but Dice says that while speed without guardrails might create advantages for some, it’ll create anxiety for others. Similar to pay transparency, organizations must practice AI transparency. Yet fewer than half of employers report having formal AI policies in place to govern or dictate its use in the enterprise, adds Dice.
AI gender gap emerges
While there’ve been efforts to move the needle on gender diversity in IT and tech over the years, AI has revealed another gender bias the tech industry will need to contend with to reach gender parity. Tech has always struggled with gender equity despite concerted efforts to make IT and STEM jobs more appealing to women.
Unfortunately, despite efforts to create cultural shifts, AI has once again widened the gender gap in tech. According to further data from LinkedIn Research, women only accounted for 26% of AI hires in the US in 2025, compared to 50% of hires into non-AI roles. And of course, the numbers drop more at the C-suite level, where only 13% of AI leadership at AI companies is held by women.
AI roles have also largely gone to candidates with college degrees with 91% of AI workers holding a bachelor’s degree or higher, moving up to 95% for C-suite and director level positions, so there’s an additional lack of opportunity for those women without a traditional education. Tech and IT leaders will need to avoid falling back into the old hiring patterns that initially caused an absence of representation in tech.
Plus, there’s an emerging gender gap on AI sentiment, with women holding more negative views than their male peers when asked about the impact of AI over the next 20 years, according to data from Pew Research. Women were more likely to say they felt negatively about the impact of AI on themselves personally (33%) and on society overall (43%), compared to 27% and 36% of men who said the same, respectively. Inversely, only 11% of women said they felt positively about AI’s impact on society, while 22% of men said they felt positive.
Women are also more likely to say AI is advancing too quickly — 68% compared to 58% of men. These opposing sentiments might contribute to the overall gender gap in AI roles, as women show more hesitation and caution with AI tools compared to male colleagues.
The IT job hiring market appears to remain strong, as data from the Dice September 2026 Jobs Report shows that IT job postings continued to increase through September after experiencing a slight dip in August. Overall, the data shows that year over year, IT job postings rose 17% compared to September 2025.
Two areas that saw the most growth include AI and ML, where tech postings grew 88% in September 2026 compared to 2025, about five times faster than the average growth
The IT job hiring market appears to remain strong, as data from the Dice September 2026 Jobs Report shows that IT job postings continued to increase through September after experiencing a slight dip in August. Overall, the data shows that year over year, IT job postings rose 17% compared to September 2025.
Two areas that saw the most growth include AI and ML, where tech postings grew 88% in September 2026 compared to 2025, about five times faster than the average growth rate for tech postings. As employees embrace AI tools and organizations realize AI implementation goals, they’re shifting a hiring focus to security and finance roles, helping to manage and oversee emerging risks and threats as AI becomes commonplace.
With this increased focus on security and finance, organizations are realizing their AI implementation strategies. And for companies ahead of the AI curve, the focus is now on cybersecurity, governance, responsible and ethical AI use, and financial operations to support AI costs.
Skills that matter most
AI skills continue to grow in demand year-over-year and month-over-month. September saw a sharp rise in demand for Claude skills and those including agentic AI, enterprise integration, and the ethical and responsible use of AI. These skills reflect similar patterns that show in the June data, suggesting they continue to be skills consistently in demand for tech workers.
Comparing skills month-to-month, there were slight changes in demand, but electronic engineering remained the fastest growing skill since July, and skills for managing AI systems grew over September. There was also an increase in IT job postings from those looking for skills including creative problem solving, team performance management, and demonstration skills.
As AI implementation takes hold and presents new risks and challenges to IT departments across every industry, companies are also shifting focusing on cybersecurity and critical thinking skills. September saw an increase in demand for endpoint detection and prevention, as well as financial technology, indicating companies are looking for talent to manage the security and cost of AI processes and tools.
The highest growth in demand over the past year are skills involving:
Claude AI (1033%)
Agentic AI (446%)
Responsible AI (401%)
Enterprise integration (376%)
AI agents (308%)
Product family engineering (295%)
AI infrastructure (283%)
Tooling (277%)
Engineering practices (277%)
AI adoption (276%)
Month over month, the Dice report’s list of fastest growing skills includes:
Electronic engineering (64%)
Autodesk Revit (57%)
Endpoint detection and prevention (51%)
Creative problem solving (51%)
Database management systems (49%)
Team performance management (48%)
Data migration (45%)
Demonstration skills (44%)
FinTech (43%)
Hot hiring markets
In terms of metro areas seeing the fastest increases of job postings, not much has changed since June’s report. However the Washington-Arlington-Alexandria (DC-VA-MD-MW) area did pull ahead of New York-Newark-Jersey City (NY-NJ) metro areas, where IT job postings dipped from over 20,000 in June to just over 16,000 in September. IT job postings in metro Dallas, Chicago, and San Francisco have remained relatively unchanged since June, demonstrating potential hiring stability in these areas.
AI skills continue to drive IT job postings, with 75% of US technology openings requiring AI fluency in June, up 178% year-over-year, according to the Dice July 2026 Jobs Report.
Roles in the software industry continue to rise, ranking second behind consulting as the industry seeking the most IT help right now. Aerospace/defense, finance/banking, and manufacturing round out the top five.
Most sought after in the market right now are software engineers, data engineers, systems engineers, electrical engineers, business analysts, data scientists, network engineers, systems administrators, data analysts, and AI engineers, according to Dice.
While these roles remain in high demand, the biggest shift can be seen in the skills that hiring managers are seeking — a list now dominated by AI or AI-adjacent skills as companies rush to adopt enterprise AI tools and services.
The skills that matter most
Demand for enterprise integration skills grew 638% from June 2025 to 2026, the biggest rise year over year, according to Dice, noting that this aligns with other indicators that “connecting agentic systems to existing infrastructure is growing faster than the agentic systems themselves.”
Following in terms of highest growth in demand over the past year are skills involving:
Agentic AI (587%)
AI agents (503%)
Responsible AI (495%)
AI infrastructure (366%)
Vector databases (353%)
Event-driven programming (310%)
Product family engineering (287%)
Prompt engineering (253%)
Observability (251%)
Month over month, the list of fastest growing skills in Dice’s July jobs report includes:
Electronic engineering (69%)
API system integration (58%)
LDAP (55%)
Digital forensics (54%)
Data exchange (53%)
Enterprise integration (50%)
Threat detection (48%)
NIST Cybersecurity Framework (47%)
SAML (45%)
Again, the rise in demand for API, data exchange, and integration skills highlights the recent push to “connect AI systems to enterprise data and workflows,” according to Dice.
Hot hiring markets
Some metro areas are seeing faster increases in tech job postings, with a focus around the New York, Washington, Dallas, Chicago, and San Francisco metro areas. These areas have seen greater growth than the rest of the country, making these metro areas the best to live in if you’re a job seeker with AI fluency skills:
Metro area
IT job postings (June)
New York-Newark-Jersey City, NY-NJ
20,858
Washington-Arlington-Alexandria, DC-VA-MD-WV
19,906
Dallas-Fort Worth-Arlington, TX
11,932
Chicago-Naperville-Elgin, IL-IN
9,346
San Francisco-Oakland-Fremont, CA
8,699
Credit: Dice July 2026 Jobs Report
New Jersey (64%), Maryland (47%), and Illinois (41%) are the states that have seen the highest year-over-year increase in hiring.
Roles in demand
Companies are looking for enterprise systems and consulting managers, including Appian developers, Oracle Cloud financial consultants, ServiceNow managers, principal consultants, and technology consultants. Additionally, they are seeking out IT software engineers, C++ software developers, configuration analysts, support engineers, network infrastructure engineers, AI analysts, and cyber threat intelligence analysts.
Outlook
Businesses inside and outside the tech industry will continue to seek tech workers to help realize AI visions, requiring a wide range of AI fluency and skills. It seems this trend will continue for the foreseeable future, as the job market slowly recovers from several tumultuous years.
North Korean IT workers are paying Americans to help them get and keep remote jobs at U.S. companies, the FBI said in an updated FBI public service announcement. At the same time, the Justice Department announced charges, two arrests, and the seizure of about 187 computer devices linked to the scheme.
The FBI said these workers use stolen identities, extort victims, and threaten physical violence to demand payments. North Korea's government receives an estimated 85 to 90 percent of the revenu
North Korean IT workers are paying Americans to help them get and keep remote jobs at U.S. companies, the FBI said in an updated FBI public service announcement. At the same time, the Justice Department announced charges, two arrests, and the seizure of about 187 computer devices linked to the scheme.
The FBI said these workers use stolen identities, extort victims, and threaten physical violence to demand payments. North Korea's government receives an estimated 85 to 90 percent of the revenue they generate, money that helps fund its nuclear weapons and other military programs.
How North Korean IT Workers Use American Facilitators
According to the FBI, North Korean IT workers are hiring Americans for a growing list of tasks. These include appearing on camera, sitting for job interviews, verifying fake identities, lending social media or professional networking accounts, shipping packages, completing urinalysis tests or fingerprint submissions, and keeping work laptops online from their homes.
[caption id="attachment_114769" align="aligncenter" width="600"] Image Source: FBI Cyber Division[/caption]
The FBI said some workers deliberately target people under financial stress, looking for those more likely to follow instructions without questions if paid. Taking part in these activities is illegal.
Home setups that host company laptops, known as laptop farms, have helped the workers hide their locations for years. The FBI said they now run more laptop farms with fewer laptops at each to avoid single points of failure. Some also land remote IT jobs and then subcontract the work to freelancers in Pakistan, India, Nigeria, or nearby countries for a fraction of the salary.
Extortion, Threats, and Identity Theft
Identity theft sits at the center of the scheme. Most names and addresses given to employers come from stolen identities, and workers often buy accounts from identity verification providers to check that stolen details will pass background checks.
The FBI said that after being fired, some workers made death threats against former managers and their families to collect more money. Others threatened to leak sensitive corporate data unless paid large lump sums. Some hired U.S.-based facilitators to show up in person at victim companies to intimidate staff.
The workers also target jobs requiring U.S. government security clearances, positions with cleared defense contractors, and active-duty U.S. military members to host laptops.
Justice Department Charges Linked to North Korean IT Workers
In Ohio, a four-count indictment charges a scheme that ran from 2019 to around July 2025. U.S. nationals Michael James Bostelle of Pennsylvania and Juan Cecilio Pena Carrillo of Texas were arrested. Ten China-based individuals were also charged, and two more defendants remain under seal.
Prosecutors say the scheme affected more than 70 U.S. employers and generated about $3 million, believed to have gone to sanctioned DPRK-controlled entities. Victims included health care, communications, cyber support, retail, and manufacturing firms across Ohio, 16 other states, and the District of Columbia.
Under Operation Lonestar Roundup, the FBI carried out searches and other actions at more than 40 Texas residences between Sept. 21 and Sept. 25. Agents seized about 187 laptops and KVM devices. Cybersecurity firm CrowdStrike tracks the group as "Famous Chollima.
FBI Cyber Division Assistant Director Brett Leatherman said 14 individuals have been charged and called close coordination with the private sector central to the operation.
What Companies Should Know About North Korean IT Workers
The FBI said no single red flag reliably identifies North Korean IT workers. It recommends an "identity in depth" approach, using layered checks throughout employment. Warning signs include remote desktop tools such as AnyDesk and TeamViewer, KVM over IP devices like TinyPilot and PiKVM, unrelated software on work devices, and frequent changes in bank accounts or addresses.
Using E-Verify, requiring a U.S. passport, and live identity checks can add friction, the FBI said, while relying only on name ban lists may block real applicants.
Individuals who receive threats should call 911. Victims or anyone approached can contact a local FBI field office and file a complaint at www.ic3.gov. The State Department has offered rewards of up to $5 million for information that disrupts North Korea's illicit financial activities.
I run interviews every week. Around minute 25, I ask about customer-facing experience. Have you sat in front of the people who use what you build? The answer I get most often: “That’s not really my cup of tea.”
A few minutes later, I ask a Python engineer which metrics he’d use to autoscale the service he just described. “That’s more of a DevOps question.”
Two answers. Same excuse. There’s a border, and the candidate has decided everything on the other side belongs t
I run interviews every week. Around minute 25, I ask about customer-facing experience. Have you sat in front of the people who use what you build? The answer I get most often: “That’s not really my cup of tea.”
A few minutes later, I ask a Python engineer which metrics he’d use to autoscale the service he just described. “That’s more of a DevOps question.”
Two answers. Same excuse. There’s a border, and the candidate has decided everything on the other side belongs to someone else.
Before tech, I captained a warship. 20 people, 30 months at sea. Out there, you master skills that have nothing to do with your specialty, because a ship where everyone stays in his lane and nobody talks to the next station is a ship that sinks. “Not my cup of tea” doesn’t exist at sea. So, when I hear the border excuse in an interview, I don’t hear a preference. I hear a ceiling the candidate built himself.
The market flipped, and the candidates didn’t
LinkedIn’s Most In-Demand Skills report put communication at number one for 2024, second year running, above every hard skill on the list. Its Skills on the Rise report for 2026, built from a billion member profiles, puts AI literacy at the top of the technical side, while soft skills take seven of the top ten spots overall, including conflict mitigation and public speaking.
None of this is new, either. Harvard economist David Deming showed it back in 2017: between 1980 and 2012, the jobs that run on human interaction expanded their slice of the American workforce by 12 points. The loner jobs built on pure math, plenty of STEM in there, lost ground. AI didn’t start the fire. It poured fuel on it.
Meanwhile, the skill we spent 20 years paying a premium for is getting commoditized in real time. Developers themselves put the figure at 42% of their committed code now being written or assisted by AI, up from 6% in 2023, per Sonar’s State of Code survey. At Cloudflare, 97% of the engineering org now codes with AI tools, and every production code contribution gets reviewed by autonomous AI agents. That came from their Q1 2026 earnings call, not a keynote. Companies can hype a keynote. They get sued over an earnings call.
A large slice of what a mid-level engineer did in 2019 is now a prompt and a review. I don’t need to convince a CIO of that in 2026. The invoices already did.
The typing got cheap. The judgment didn’t.
To be clear, nobody commoditized deep technical understanding. What got cheap is the typing. And the moment typing got cheap, judgment got expensive. Somebody still has to decide what deserves to be built, what gets skipped and which team burns its budget on which problem. A model spits out options all day long. It won’t pick one for you. That call needs a human who understands the whole board, and those humans are exactly what the silo never produces.
Which is why that ceiling from the interview room is so loud. An engineer who caps his own understanding in 2026 is announcing he hasn’t understood what’s happening around him.
Code got cheap. Talking got expensive. Nobody repriced their career.
So, what’s rare now? The engineer who can walk a VP of Sales through a tradeoff without once mentioning the stack. The one who can take an angry customer’s call, all 40 minutes of it, and stay curious instead of defensive. Every year my interviews surface fewer people who can pull off either one. No study backs this. My notes do.
How we got here
Covid killed the hallway and we buried it with a hybrid policy. The arguments at the whiteboard, the “got a sec?” over someone’s shoulder, they all migrated into Slack. Problem is, nobody can grab your shoulder in Slack. You can go dark for a whole day, and the tool calls it focus.
Then the productivity religion redefined talking as a waste. I’ve read the books; some of it is right. But a whole generation absorbed the gist without the nuance, and the gist is: every human interaction is an interruption. A customer call is somebody else’s job.
We made it worse ourselves. Twenty years of interview loops built around algorithm puzzles selected, at scale, for people who perform best alone with a screen. Then we act surprised they’d rather be alone with a screen. And we split teams by tool instead of by problem. Python people here, Kubernetes people there and when a request landed on the seam, we invented a word for the seam. DevOps was supposed to be a culture. It became a tag you put on a ticket, so it stops being yours.
And at some point, the teams inside the building started acting like strangers doing business. The team next door stopped being colleagues and became “a service we consume.” You file a ticket, you wait for the SLA, you never hear a human voice. With an outside provider, fine, that’s the deal. Inside one company, on one platform? That’s two crews on the same ship passing notes under the door. Somewhere along the line we decided a 10-minute conversation costs more than a three-day ticket loop.
That’s on us. On CIOs, on CTOs, on CEOs, on me.
The perfect colleague
Then AI showed up as the perfect colleague. Never interrupts. Never needs the context twice. Never has an opinion you didn’t ask for. Never makes you feel stupid for asking. Available at 2 AM, and I have tested that more times than I should admit. And it’s addictive in a way nothing in this job has been before. You open the IDE, you describe, the thing appears, you push, you describe the next thing. Hours go by. Nobody interrupted you, and nobody disagreed with you. Feels like the most productive day of your career. Some days it is. I feel the pull myself, and I have been managing people for more than 22 years.
Thing is, it compounds. Communication is a muscle, and the reps used to come for free: the standup, the design argument, the customer who called because the ticket wasn’t clear, the product manager who wanted it explained again. Every one of those reps now has a substitute that doesn’t talk back. Reps drop to zero. Muscle goes. The next customer call feels harder than the last one, so you avoid it a bit more, so the muscle goes faster. Nobody decides to get worse at talking to people. It happens one quiet, very productive day at a time.
Twelve months of that and a senior engineer who used to run design reviews can’t hold a room. He won’t notice. His manager will.
So, we need generalists now?
Wrong conclusion, and I hear it from CIOs weekly.
We don’t need generalists. We need people willing to level up. To combine pieces, they never had to combine, because for 20 years the org chart did it for them. The barrier has never been lower. It used to take a course and a colleague with spare time. Now it takes a model and the willingness to ask. The excuse is gone.
Does that make you less of a specialist? Of course not. It makes you a better one, because the silo was constraining your understanding, and you couldn’t see it from inside.
The autoscaling question. Which metrics actually drive scaling for the service you wrote, and why those? People park it one desk over. A software engineer should own it, because every answer depends on the code he wrote. A senior should have known before I asked.
AI made breadth cheap. The specialist’s excuse died. The specialist didn’t.
The ones who ignore all this won’t get fired. Nothing that dramatic. Their work will simply dry up around them. The product manager who used to bring them questions now asks the model instead. Fewer requests land on their desk. Their salary stops moving. Then one day they test the market, search for “Python developer” openings, and find the titles changed while they weren’t looking. Firms now ask for web engineers, people who own the whole picture, front to back. Nobody sent a memo. The market repriced the role quietly, while they kept their head down in their lane.
The customer border
Not long ago I had a problem with a flight and spent days trying to reach my airline. Every path led to a bot. No phone number for a human anywhere, and my case was the one in a million the flows were never built for. I ended up driving to the airport to talk to a person at a desk. Think about that. I build conversational AI for a living and even I couldn’t find the human. The bots handled the million. The airport desk handled me.
Years around customer experience taught me to admit this out loud: there are moments a customer needs a person. When the system is down at 11 PM and the quarter closes tomorrow, nobody wants a knowledge base. They want a human who owns the problem and says so. You can’t prompt your way through an angry customer. And you can’t force people to stop feeling human when things go wrong. Sentimental beings, all of us. That need is not going anywhere.
I know exactly where the bot stops and the human starts, because that handoff is the product I build. The engineer who never sat in the escalation queue designs that moment from a spec sheet. The one who sat there writes different code. Different priorities. Fewer features nobody asked for.
The bot gives you the answer. The customer gives you the problem you didn’t know you had. Only the second one compounds into judgment.
Customer-facing is not sales
Part of the resistance, and I see this in interviews constantly, is a misunderstanding. Engineers hear “customer facing” and think sales. They picture memorizing everything, defending the firm with skills they don’t have, performing some salesy theater. Wrong on every count. Customers reward honesty. They respect the engineer who says, “I don’t know, let me check” and actually comes back. And customers idolize the tech people who visibly care about their problem, because that is rare.
I watched it happen recently. In a QBR, the quarterly review we run with customers, one of them asked for a technical representative in every meeting going forward, next to the project side. I added an architect to the rotation. The customer loved it. The architect gained more. He was doing this work already, just never in front of the people paying for it. Now he had to structure his thinking, prepare and answer live questions with no editor between him and the room. He leveled up within a quarter. The runbooks existed before. The documentation existed. What changed was one man willing to step out of his comfort zone and take pride in his work in front of the people who use it.
So, should engineers run customer sessions? The willing ones. And here I’ll argue with an earlier version of myself, because I used to think you assign this like a watch bill, the duty roster of a ship. You can assign exposure. You can’t assign mastery.
On my ship, the officers who grew into command were never the ones I had to push toward the bridge. They were the ones already up there off duty, asking about the next qualification. Same in engineering. Introvert is a personality. Unwilling is a decision.
Four moves, starting Monday
Change the interview loop. Add one round where the candidate explains his system to someone outside tech and gets interrupted with naive questions. Then ask him something one desk over from his specialty. Watch the reaction. The reaction is what you’re hiring.
Coach the ones who raise their hand. Some engineers struggle in front of customers, know it and want to fix it. Give them real budget: training, shadowing, a debrief after every session. Film review, like athletes do. Nothing you fund this year will return more.
Stop persuading the rest. If someone needs a campaign to see why this matters, he will never put in the work the skill demands. Nobody masters a craft he was talked into. Spend that energy on the willing.
Organize by problem, not by tool. If a customer request always needs two teams and a handoff, fix the org chart, not the request. And kill the internal vendor act. One platform, one crew.
The part nobody wants to hear
Communication was never a soft skill. We just called it that while code was the expensive thing. Code isn’t expensive or scarce anymore. What’s left is the muscle we let atrophy and the border we let people hide behind.
AI can accelerate everything except experience. Sitting with a human who’s frustrated with your product still takes reps.
Organizations continue to invest heavily in the cloud, with IT leaders reporting that 26% of their IT budget will be allocated to cloud computing within the next year, according to the 2026 Foundry Cloud Computing Study.
The survey also found that 74% of IT leaders have accelerated cloud migrations in the past 12 months compared to 70% in 2025 and 63% in 2024. Three in four (73%) also said cloud capabilities have helped their organizations achieve “increased and sustainabl
Organizations continue to invest heavily in the cloud, with IT leaders reporting that 26% of their IT budget will be allocated to cloud computing within the next year, according to the 2026 Foundry Cloud Computing Study.
The survey also found that 74% of IT leaders have accelerated cloud migrations in the past 12 months compared to 70% in 2025 and 63% in 2024. Three in four (73%) also said cloud capabilities have helped their organizations achieve “increased and sustainable revenue over the past 12 months.” Overwhelmingly, 80% of respondents from North America and APAC noted that their cloud strategies have helped accelerate the adoption of AI, while that number drops to 68% for the EMEA region.
This growth in cloud adoption, along with accelerated interest in AI, has sparked an increased demand for certain cloud roles. Here are the roles companies are most likely to have added to support their cloud investments, according to Foundry’s research.
The role of AI/ML engineer is in high demand as organization expand their AI strategies. These professionals design and implement AI and machine learning systems, overseeing them in operation to identify opportunities for improvement, ways to better automate processes, and how to better inform decision-making across the organization.
Skills: Skills for this role include programming, knowledge of machine learning, data science, data engineering, and experience building AI systems using APIs. See also: “The hidden skills behind the AI engineer.”
Role growth: 36% of companies have added AI/machine learning engineers as part of their cloud investments, according to Foundry’s survey.
AI platform engineer
An AI platform engineer is responsible for building and running the internal systems that businesses use to build and scale AI tools and initiatives. As organizations increasingly adopt AI internally, they’re hiring professionals to help navigate the daily operations of internal developer platforms (IDPs) that use AI to boost productivity and drive automation.
Skills: Skills for this role include understanding of cloud infrastructure, programming languages, and orchestration and container technology, including Kubernetes and Docker.
Role growth: 27% of companies have added AI platform engineers as part of their cloud investments.
Cloud architect
As cloud computing grows increasingly complex, cloud architects have become vital for navigating the nuances of implementing and maintaining cloud environments. These IT pros can help organizations avoid cloud security risks, while also ensuring a smooth transition to the cloud. With 65% of IT leaders choosing cloud-based services by default when upgrading technology, cloud architects will only become more important for enterprise success. For those interested in this role, see “IT career roadmap: Cloud architect.”
Skills: Skills for this role include knowledge of application architecture, automation, ITSM, governance, security, and leadership.
Role growth: 21% of companies have added cloud architect roles as part of their cloud investments.
Cloud software engineer
Cloud software engineers are tasked with developing and maintaining software applications that run on cloud platforms, ensuring they are built to be scalable, reliable, and agile. Companies that have migrated to the cloud often need IT pros who can build company-specific services and applications to make the most of the cloud environment. For more on this career path, see “IT career roadmap: Cloud engineer.”
Skills: Relevant skills for a cloud software engineer include Python, Java, C#, JavaScript, microservices architecture, serverless computing, APIs and SKDs, DevOps, cybersecurity, and knowledge of the agile methodology.
Role growth: 20% of companies have added cloud software engineer roles as part of their cloud investments.
Cloud developer
Cloud developer is a vital role for developing and deploying software in cloud environments. These IT pros are tasked with designing, creating, and deploying applications designed to run on cloud platforms, with a focus on building scalable, reliable, and cost-effective solutions to meet business needs.
Skills: Relevant skills for a cloud developer include programming languages such as Java, C#, and Python as well as knowledge of popular cloud platforms, microservices architecture, database storage, agile methodology, APIs and SKDs, and containers and orchestration.
Role growth: 20% of companies have added cloud developer roles as part of their cloud investments.
Security engineer
Security engineers are tasked with overseeing the security of an organization’s systems, networks, and data, to make sure they’re protected from cybersecurity threats. For organizations investing in the cloud, security engineers can help ensure services, applications, and data running on cloud platforms are secure and compliant with any government regulations.
Skills: Network security, IAM, encryption, vulnerability management, security architecture, cloud security, automation, and infrastructure design and optimization.
Role growth: 19% of companies have added security engineer roles as part of their cloud investments.
Cloud consultant
With the rapid adoption and move to the cloud, organizations look for professionals who can leverage cloud technologies to meet business needs, grow the business, and improve efficiency. Cloud consultants are cloud experts who stay on top of the latest innovations in cloud technology to better advise business leaders.
Skills: Knowledge of architecture and solution design, DevOps, automation, project management, cloud security, compliance, cloud migration, and knowledge of popular cloud platforms.
Role growth: 16% of companies have added cloud consultants as part of their cloud investments.
Security architect
Security architects are responsible for building, designing, and implementing security solutions in the organization to keep IT infrastructure secure. For security architects working in a cloud environment, the focus is on designing and implementing security solutions that protect cloud-based infrastructure, data, and applications.
Skills: Security architecture design, network security, security compliance and governance, incident response and forensics, data encryption, IAM, automation, and DevSecOps.
Role growth: 16% of businesses have added security architect roles as part of their cloud investments.
Cloud product manager
With cloud adoption often comes an increase in in-house development of cloud-based services. A cloud product manager can help cloud teams develop effective solutions aimed at fulfilling business objectives. They’re also tasked with using their deep understanding of product management within the cloud environment to work closely with key stakeholders, identify and define requirements from users or customers, develop product roadmaps, and oversee the QA process to gain feedback on how to improve product offerings.
Skills: Product management, UX design, communication and collaboration, and a strong technical background.
Role growth: 16% of organizations have added cloud product manager roles as part of their cloud investments.
Cloud governance/compliance manager
Cloud governance and compliance managers help companies navigate the complexities of security, governance, international regulation, and internal policies. They identify potential risks, implement automated tools to oversee security and compliance, and help businesses maintain secure cloud operations.
Skills: A strong knowledge of regulatory policies such as GDPR, HIPAA, PCI DSS, and other international data protection laws. Additional skills include knowledge of tools such as CSPM, Azure, AWS, Microsoft Purview Compliance Manager, and other IT governance tools.
Role growth: 16% of businesses have added cloud governance and compliance manager roles as part of their cloud investments.
Cloud network engineer
Cloud network engineers are responsible for the design, implementation, and management of an organization’s cloud-based networks. These IT pros are tasked with overseeing network management, virtualization and virtual LAN, wide area networks, TCP/IP, HTTP, network security, and the integration of hybrid cloud and multicloud deployments.
Skills: Relevant skills for this role include knowledge of cloud platforms such as Azure, AWS, Google Cloud, along with networking fundamentals, virtualization, project management, security, automation and scripting, and collaboration.
Role growth: 15% of companies have added cloud network engineer roles as part of their cloud investments.
Data architect
A data architect’s focus is seeing that an organization’s data is structured so it can be easily accessed, secured, and efficiently stored, and that it meets business needs. Data has become a primary way for businesses to conduct analysis and assist with business decision-making, and most of that data is now stored in the cloud.
Skills: Data warehousing, scalability and performance optimization, automation and virtualization, data governance and cloud security, data migration, and knowledge of hybrid cloud solutions.
Role growth: 14% of businesses have added data architect roles as part of their cloud investments.
Prompt engineer/AI application developer
Prompt engineering and AI application development go hand in hand, and they’ve become vital skills for organizations that have embraced AI and plan to implement AI-focused services and into daily workflows. Prompt engineers are responsible for designing and refining the instructions and structural queries, while an AI application developer builds software system and user-interfaces for AI-ready software and services.
Role growth: 14% of companies have added prompt engineering and AI application developer roles as part of their cloud investments.
Cloud platform engineer/platform ops
Cloud platform engineers, who often work in platform operations, are responsible for building and maintaining cloud tools, automated systems, self-service portals, and other software that developers use to test code. In this capacity, they’re responsible for creating user-friendly platforms for other engineers in the company to build and test their own software for clients and customers.
Skills: Skills for this role include infrastructure as code (IaC), containerization and orchestration, scripting and coding, and Linux and networking.
Role growth: 14% of companies have added cloud platform engineering roles as part of their cloud investments.
MLOps engineer/AI operations engineer
The role of MLOps engineer or AIOps engineer has been developed to help close the gap between data science and IT operations. It’s a role that has emerged as the use of AI increases, as organizations need a point person who has expertise in IT operations and machine learning, and is comfortable collaborating with data scientists, developers, IT operations staff, and key stakeholders.
Skills: Skills for this role include programming, DevOps, cloud tools, containerization and orchestration, and knowledge of ML tools.
Role growth: 13% of companies have added MLOps engineers as part of their cloud investments.
Cloud sysadmin
Cloud systems administrators are charged with overseeing the general maintenance and management of cloud infrastructure. Whether that means implementing cloud-based policies, deploying patches and updates, or analyzing network performance, these IT pros are skilled at navigating virtualized environments. Cloud sysadmin is likely the most entry-level-friendly role on this list.
Skills: An understanding of implementation and integration, security, configuration, and knowledge of popular cloud software tools such as Azure, AWS, GCP, Exchange, and Office 365.
Role growth: 13% of companies have added cloud systems admin roles as part of their cloud investments.
DevOps engineer
DevOps focuses on blending IT operations with the development process to improve IT systems and act as a go-between in maintaining the flow of communication between coding and engineering teams. It’s a role that focuses on the deployment of automated applications, maintenance of IT and cloud infrastructure, and identifying potential risks and benefits of new software and systems.
Skills: Automation, Linux, QA testing, security, containerization, and knowledge of programming languages such as Java and Ruby.
Role growth: 11% of companies have added DevOps engineer roles as part of their cloud investments.
FinOps/cloud cost optimization practitioner
FinOps and cloud cost optimization practitioners combine knowledge of finance, technology, and businesses to help oversee the increasingly complex landscape of cloud investments. Cloud computing is integral to AI, so as more organizations invest in it, they’re also revisiting investments in cloud infrastructure. FinOps and cloud cost optimization practitioners can help guide organizations to make the right financial decisions around technology investments that’ll impact the business.
Skills: Knowledge of finance, business, and technology along with skills using tools and platforms including AWS, Azure, GCP, and cloud-native FinOps platforms.
Role growth: 9% of companies have added FinOps and cloud cost optimization practitioner roles as part of their cloud investments.
Site reliability engineer
For any organization implementing cloud strategies, there’s a significant focus on reliability and scalability, ensuring that data can be accessed from the cloud and on-demand as needed. Site reliability engineers (SREs) are responsible for overseeing automation of IT infrastructure, application monitoring, and system management. Cloud infrastructure requires frequent software updates, and services must be able to scale with the organization’s growth.
Skills: Change management, IT infrastructure management, emergency incident response, process improvement, and application monitoring.
Role growth: 8% of companies have added site reliability engineer roles as part of their cloud investments.
FinOps lead/FinOps manager
FinOps leads and FinOps managers are tasked with overseeing the intersection of engineering, finance, and business. As more organizations build cloud services and tools, they’re looking for FinOps professionals with technical knowledge to help bridge the gap between finance and tech, bringing better insights into ways to cut costs and stay on budget while implementing innovative technology.
Skills: FinOps leads and managers need a strong understanding of engineering, finance, and technology. Additional skills include knowledge of cloud platforms, basic coding skills, and data analytics.
Role growth: 6% of companies have added FinOps lead and FinOps manager roles as part of their cloud investments.
As cloud experience becomes more critical to organizations hosting AI-powered services, tools, and software, these cloud roles and skills will become increasingly in-demand. Now is an opportune time to seek out valuable cloud certifications and other relevant AI and ML certifications to boost your resume, and set yourself up for these emerging and established career paths.
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