Entry-level hiring in technology roles has declined by 15% to 20% in large enterprises as artificial intelligence automates routine tasks, even as demand shifts toward higher-skill roles.
“There has been at least 15% to 20% reduction in entry-level jobs in Fortune 500 companies,” Vijay Swaminathan, CEO of agentic intelligence company Draup told CybernetIX. “Managers are finding it harder to define meaningful work for fresh hires as AI takes over repetitive tasks.”
The decline is most visible in application development and quality assurance roles, where AI tools are increasingly taking over basic coding, testing, and routine engineering work that was traditionally assigned to junior employees, according to Swaminathan.
As enterprises embed AI more deeply into day-to-day workflows, tasks that once served as a training ground for entry-level engineers are being automated, reducing the need for large junior hiring cohorts, he added.
Demand shifts to higher-skill AI and deployment roles
At the same time, overall demand for technology talent is not declining but shifting toward more specialized roles, Swaminathan said. Enterprises are increasing hiring for AI engineers, data engineers, and forward deployed engineers—professionals who work closely with business teams or customers to implement and operationalize AI systems in production environments.
Swaminathan said forward deployed engineers are emerging as a critical role as companies move from building AI models to deploying them at scale.
“These are the people who sit between engineering and the customer, helping translate AI capabilities into real-world applications,” he said, adding that demand for such roles is expected to outpace traditional AI development roles.
He added that such roles require a combination of AI, data, and domain expertise, making them harder to fill and increasingly important in enterprise AI deployments.
AI hiring concentrates in specialized roles as models evolve
Data from Draup’s analysis of job postings underscores the shift toward higher-skill roles. AI builder positions account for roughly 27% of hiring demand, followed by infrastructure roles at about 20%, forward deployed engineering roles at around 18%, and governance and guardrail-related roles at approximately 15%.
According to Swaminathan, the growing share of governance and guardrail roles reflects increasing enterprise focus on managing risks associated with AI deployments, including compliance and oversight requirements.
The shift in demand is also reshaping hiring strategies. Swaminathan said traditional campus recruitment programs are slowing, particularly for entry-level roles, as companies reassess workforce needs in an AI-driven environment.
In many cases, he said, organizations are moving toward contract-based hiring, internships, and project-oriented engagements to access specialized skills more flexibly.
“There is a move away from hiring large batches from campuses toward more targeted, skills-based hiring,” he said.
Skill mismatch, not demand decline
While the near-term impact has been a slowdown in entry-level hiring, Swaminathan said the underlying demand for technology talent remains strong, particularly for professionals with AI and data-related expertise.
“This is not a demand problem—it’s a skill mismatch problem,” he said. “The demand is there, but the nature of the skills required is changing rapidly.”
The changes are also altering career trajectories within the technology workforce. According to Swaminathan, experienced professionals with AI-related expertise are seeing strong demand and, in some cases, higher compensation, while entry-level engineers may face a slower start as companies reduce reliance on junior roles for routine work.
Layoffs and AI investments reshape workforce trends
The shift comes amid broader workforce changes across the technology sector, where companies are cutting roles while increasing investments in artificial intelligence. More than 120,000 tech workers were laid off across hundreds of companies in 2025, according to industry trackers.
Several large firms, including Salesforce, Oracle and Amazon, have linked job reductions to efficiency gains from AI or to reallocating resources toward AI infrastructure and development.
Even so, Swaminathan said the long-term outlook remains positive for those able to adapt to changing skill requirements, as enterprises continue to expand their use of AI across business functions.
