Reflecting on his career journey, Hazarika said that AI is no longer considered as an option to improve productivity. Instead, most technology companies now expect their engineers to actively use AI tools to accelerate development, manage repetitive coding tasks, and improve code reliability. He noted that this change allows engineers to spend more time on system architecture, complex problem solving, and business-critical logic.
Software Engineering Interviews: Then and Now
In an interview with Business Insider, Hazarika explained that preparing for software engineering roles today is much different than it was five years ago.
In 2020, he said, being good at interviews for data structures, algorithms, and system design was often enough to stand out. These features are now considered basic expectations rather than differentiators. Problem-solving skills, scalability knowledge, and cloud expertise remain essential, but candidates are also expected to understand prompt engineering, AI-assisted debugging, and AI integration strategies.
Employers are increasingly looking to engineers who can decide when to rely on AI-driven solutions and when a traditional approach is appropriate.
AI tools become part of live coding interviews
Hazarika pointed out that the interview format itself has evolved. Some companies now allow and even encourage candidates to use AI tools during live coding rounds.
Recalling one such experience, he shared how an interview with a Silicon Valley startup in 2024 was a turning point in his thinking. During the interview, he was given a large existing codebase to debug and was explicitly allowed to use AI tools. He chose not to rely on AI and ultimately failed the interview. He called the experience a wake-up call.
System design and action rounds have also changed
System design interviews are no longer limited to just scalability and architecture. Hazarika said he is seeing more questions about AI integration, infrastructure planning and lifecycle management of machine learning models.
Behavioral interviews, on the other hand, are now focused on how candidates assess AI usage, manage risk, and strike the right balance between automation and human oversight in production systems.
Advice for people aiming to become engineers
Hazarika advises future software engineers to position themselves as hybrid professionals, combining strong engineering fundamentals with practical AI expertise. He said the most competitive candidates will be those who can seamlessly blend the core principles of software with practical, real-world applications of artificial intelligence.
