Where did you go to school?
San Francisco State University
What was your favorite class there?
I took a microbiology class on infectious diseases that I really enjoyed.
What was your favorite late-night food?
Noodles!!
Why did you apply for the internship at Ripple?
When I read the job description, I liked that it was so open-ended. When I spoke with the hiring manager, it seemed like Ripple was a place where I would have a lot of freedom to work on projects that solved a wide range of problems. I liked the idea that I wouldn't be pigeonholed into a very specific function or area. It seemed like I would get exposed to a range of projects and technologies which felt different from my past internship experiences.
Were you involved with digital assets or blockchain at your school?
Nope. My only experience with financial technology had been working at the Federal Reserve of SF and I had felt frustrated by the slow pace and restrictions there. I thought I might have a better experience working at a private company (especially a startup) where there's more flexibility and appetite for innovation.
What was your biggest surprise as an intern?
I was surprised by how much I felt like a true member of the team. I didn’t feel like I was “just the intern”.
What was the hardest problem you solved as an intern?
I think the hardest part about being an intern was getting used to being constantly outside my comfort zone. Interning at Ripple exposed me to new tools and technologies that I didn’t have any prior experience working with, which was both exciting and challenging.
How long have you been a permanent Ripple employee?
I was an intern for a little less than three months. At the end of August 2019, became a permanent Ripple employee.
What's the biggest difference between being an intern and a permanent employee?
Getting to work on larger, longer-term projects. Getting to be more involved in the design process.
What problems are you solving now as a full-time “Rippler”?
One of the projects I’m working on now automatically generates example API requests and responses using unit tests. This helps the documentation team as it prevents them from having to manually generate these examples themselves. It can also help us catch breaking changes in the code if any of the tests fail.