Akaash Vishal Hazarika, a 29-year-old senior software engineer based in Seattle, has spent the last eight years in the tech industry, with experience at major companies such as Google, Amazon, Splunk, and Salesforce. Hazarika has observed significant shifts in the skill sets required for software engineers, particularly as artificial intelligence (AI) integrates deeper into the software development process. As technology companies increasingly recognize the productivity gains afforded by AI, engineers are now expected to leverage these tools to expedite their workflow and enhance reliability.
Reflecting on his own path, Hazarika recalls that when he was interviewing for software engineering positions in 2020, proficiency in coding challenges on platforms like LeetCode and a solid grasp of system design were paramount. Candidates who excelled in data structures and algorithms often secured job offers. However, the landscape has changed considerably. Today, familiarity with AI is no longer an added bonus; it’s a fundamental expectation. Candidates must now demonstrate an understanding of prompt engineering and how to utilize AI for tasks like error handling and bug fixing, as well as integrating AI into existing business workflows.
Hazarika emphasizes that while core skills such as problem-solving and knowledge of cloud services remain vital, the growing reliance on AI has transformed interview processes. Applicants are still expected to possess a strong foundational knowledge of system design and algorithms. However, the advent of AI has led to new expectations. Some companies now permit the use of AI tools during live coding interviews to assess candidates’ ability to combine traditional engineering skills with AI capabilities. Hazarika recalls a pivotal moment during an interview with a Silicon Valley startup in 2024, where he was surprised to discover he could use AI assistance to debug a complex code file. Not utilizing this option ultimately led to his failure in the interview, highlighting the need for engineers to adapt to this evolving landscape.
Interviewers are also probing candidates on their ability to integrate AI within current business workflows and evaluate trade-offs between AI and traditional methods. As Hazarika notes, applicants can expect to be tasked with designing systems that incorporate AI or discussing how to leverage AI for business enhancement. Companies now often expect candidates to deliver a functional feature within an hour, a task made feasible primarily through AI tools.
To equip new graduates for the changing demands of software engineering, Hazarika advises focusing on several key strategies. First, cultivating a production mindset involves contributing to open-source projects, demonstrating the ability to navigate and enhance a collaborative codebase. Building a portfolio of AI-integrated projects showcases practical experience, while familiarity with cloud tooling and AI prompting can significantly bolster an applicant’s profile. Engaging with platforms such as AWS or GCP to obtain certifications can further illustrate an eagerness to learn and adapt.
For seasoned engineers, Hazarika suggests mapping their existing specialty with complementary AI skills. This includes backend tasks related to scaling systems and developing proficiency in critical tools for data engineering and site reliability engineering. Understanding the trade-offs of utilizing third-party APIs versus open-source solutions is essential for developing an AI product mindset. Furthermore, he encourages engineering professionals to identify areas within their current roles that could benefit from AI integration, promoting efficiency across workflows.
In conclusion, Hazarika advises that both new and experienced software engineers should maintain a sense of curiosity. As technology evolves, staying informed about the latest AI tools while retaining foundational engineering principles will continue to be invaluable in the job market. He positions himself as a ‘hybrid engineer,’ bridging the gap between pure coding and prompt engineering, a perspective that may be increasingly sought after in the industry.
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