A Day in the Life of a Software Engineer at Big Tech Company

I try to be pretty regimented with my day. I start by going through Teams, our chat platform, to check for any messages I might have received overnight.

Our team spans every time zone, so I'm constantly in contact with people in China, India, Germany, and across the US. When I wake up, people have already been working and often have many questions waiting for me.

I try to reply thoughtfully, as these questions can set the tone for my entire day. I also review my emails. Some come from my boss or team members, and there can be expectations to reply promptly, especially if there's a long thread with high-level stakeholders involved.

Other emails are auto-generated alerts for the products and features I work on. These alerts can create incidents in my inbox, flagging issues like feature problems or runtime errors in code.

More often than not, these are internal alerts, but we sometimes receive customer escalations. These take priority because they mean a customer is blocked and unable to use a product or feature. They contact an escalation engineer, who then gets in touch with us, the software engineers, to investigate. This usually takes up the first few hours of my day.

Then the real excitement begins: meetings. I can often be productive during meetings, but there are two kinds. One type expects active contribution and participation, requiring my full attention.

However, at least half of the meetings I attend are ones where I'm primarily there to listen. Something might catch my attention, prompting me to speak, but otherwise, I can work on other tasks.

After handling emails, messages, and meetings, I finally get to work on my tasks and projects. This involves hands-on coding, writing unit and integration tests, and implementing features according to specifications. I reach out to product managers for clarification when needed, especially when murky areas arise during implementation.

My coding process has changed dramatically. I'm not just coding in the traditional way, like one might have learned five years ago. There's an expectation to leverage new AI tools, making it more of a collaborative exercise.

I spend a lot of time conversing with my copilots and different data agents during this process. This is how I spend a good chunk of my day writing code, interacting with these AI tools.