engineering roles – EY says AI is compressing software delivery, pushing it toward product-first training and hiring that spans data, software and AI.
A quiet shift is reshaping one of the tech industry’s most familiar career ladders: the line between data engineering, software engineering, and AI engineering is blurring.
EY’s global consulting AI leader, Dan Diasio, argues that software engineering roles aren’t disappearing, but they are converging.. In his view. the change reflects how quickly modern engineers can build and deliver results. and how those outcomes increasingly depend on working across multiple technical disciplines rather than staying within a single specialization.
Diasio said the work itself is moving in the direction of overlap. Although the job titles may still be distinct today, he described the responsibilities of engineers as blending—especially in how teams design, develop, and refine products that rely on data and AI capabilities.
That convergence has also prompted EY to rethink how engineers are trained. Instead of focusing on traditional software engineering lifecycles, the firm is pushing toward product development lifecycles, training engineers to operate more like end-to-end product builders instead of “pure coders.”
The rationale is tied to how AI is accelerating product timelines.. Diasio described a workflow where AI-generated outputs are used earlier and more continuously—for example. when AI-generated requirements can replace the start of a requirements document process. AI-generated design planning can shape the next phase. and teams then build and code the software based on those outputs.. He said this streamlined approach is happening “much faster” than what EY could previously achieve.
EY’s comments come as a broader wave of changes has moved through the software engineering industry since late 2025.. Improvements to AI coding models—such as automated coding work by systems like Claude Code and Codex—have increasingly reduced the need for engineers to manually handle many coding tasks.. Engineers have also told the publication that they haven’t touched code directly since December.
For EY. the shift isn’t limited to how work gets done; it is also changing how the firm evaluates people it hires.. Diasio said EY is no longer simply assessing coding ability. noting that the “floor has risen.” Instead. he said the firm is looking for candidates who can go beyond the baseline and “break through the ceiling.”
During hiring interviews. Diasio indicated that EY is placing greater weight on intent—asking candidates why specific design decisions were made. what outcomes those choices were meant to solve. and how the work fits within a broader product.. He said the traits that separate top talent now include well-crafted intent, architecture thinking, and scalability.
He also emphasized that top engineers should be actively involved in the hiring process. “A talent hires A talent,” he wrote, framing recruitment as something that depends on technical excellence and judgment, not only on testing skills.
The hiring shift is arriving alongside a wider reassessment of EY’s talent strategy. From onboarding to promotions, the firm is adjusting how it develops workers as AI becomes more embedded in everyday operations.
EY’s talent chief, Ginnie Carlier, previously said AI is making career paths more fluid. Under that approach, EY requires all early-career applicants to complete skills-based assessments and is seeking candidates who can evolve with technology.
Beyond technical growth, Diasio said EY is increasing its emphasis on managerial capabilities for hires across both business and technology. He described a break from a common professional services model where junior staff primarily execute tasks until they later take on supervision roles.
In Diasio’s account, many entry-level hires are now expected to delegate and manage workflows across AI tools earlier than before. That expectation, he said, reflects the reality that as AI gets integrated into daily work, employees must think more like managers earlier in their careers.
To support that transition, Diasio said EY is allocating more training toward managerial skills. He wrote that the firm is preparing new hires to be “Day One managers,” signaling how quickly roles are expected to expand as AI reshapes delivery and execution.
The business implication is straightforward: as AI speeds up parts of the coding process. firms like EY appear to be shifting competitive advantage away from who can write code and toward who can design products. manage architecture and scale. and coordinate AI-augmented workflows end to end.. For engineers. that can mean redefining what “engineering” looks like on the job—less isolated execution. more product thinking and earlier leadership responsibility.
EY AI leader engineering roles product-first training AI coding models software development talent strategy managerial skills