It was both exhilarating and intense. The process began with a recruiter reaching out via LinkedIn after I applied through their careers portal.

The process kicked off with a 45-minute phone screen where I tackled algorithmic problems on a shared coding platform, focusing on data structures like arrays and trees, which I nailed thanks to rigorous LeetCode practice.

Advancing to the onsite rounds at their Mountain View campus, I endured a grueling day of five back-to-back interviews:

• Two on coding challenges involving dynamic programming and graph traversal.
• One on system design where I architected a scalable messaging app akin to Google Chat.
• A behavioral session delving into past projects and teamwork using the STAR method.
• Finally, a casual chat with a potential manager about company culture and my passion for AI-driven innovations.

Despite the brain-teasing puzzles and whiteboard sessions that tested my problem-solving under pressure, the interviewers were supportive and insightful, providing subtle hints when I got stuck.

Ultimately, while I didn't land the offer due to stiff competition, the experience honed my skills, offered valuable feedback on optimizing code efficiency, and reinforced my admiration for Google's emphasis on innovation and work-life balance.

It was a challenging coding question where I was asked to implement Dijkstra's shortest path algorithm. The goal was to find the minimum distance from a source node to all other nodes in a weighted graph.

I also had to explain how to use a priority queue for optimization and analyze the algorithm's time complexity.