Engineering graduates, need to crack to this AI code to get hired

Freshers aiming for jobs at top IT firms are now required to ‘refactor’ an artificial intelligence (AI)-generated code as part of the hiring process. According to a Economic Times report, “from being asked to write simple codes, candidates are being asked to optimise and restructure existing AI written codes, to improve quality”.

Experts argue that coding from scratch doesn’t align with the realities of modern software development , particularly within large organisations that rely heavily on vast code libraries and AI-driven tools. Another expert said that the 2025 onwards test will include questions on knowledge of AI coding tools as they will become coding assistants for freshers in future.

What is refactoring
Refactoring code means restructuring or reorganising an existing code without changing its external behaviour. The purpose is to improve the code's readability, maintainability, and efficiency, making it easier to understand.

The report quotes Chirag Mehta, vice president and principal analyst, Constellation Research, who said, “The focus in hiring has shifted from just programming skills to broader problem-solving capabilities….. Hiring tests for entry-level engineers are evolving to gauge candidates' ability to learn new methods, optimise existing code, and “refactor” it to improve quality. It’s about finding engineers who are agile thinkers, not just scriptwriters.”

Yugal Joshi, partner, Everest group, said, “Unlike earlier times where developers were focused more on technical aspects of software development, now other skills such as reviewing AI-generated code, assessing AI-generated documents such as, code comments, requirements, etc is important as well.” H

Addressing concerns about securing AI-generated code, Mehta explained that such code presents unique security challenges. He said “There’s a bias to trust code created by AI, but these tools are as prone, if not more, to introducing vulnerabilities as human coders. If an AI tool generates insecure code, that risk multiplies as more developers rely on it across projects. Companies must “shift left” to address security upfront—reviewing AI-generated code for vulnerabilities and rigorously validating the tools themselves. Security needs to be baked into the code generation process, ensuring that AI aids development without compromising safety, leading to security by design.”