I’m doing interviews for companies that would involve API integrations. I’ve done a couple now where I was given some general API information (some intentionally unclear, some more clear) and I felt I didn’t do well. Mainly I was nervous, and felt very pressured just to understand how the different parts of the APIs interact with each other and should be interacted with. This is despite doing this for work and myself not feeling as nervous doing more common coding tests which I don’t do as much at work(thanks to doing examples on hackerrank, Leetcode helping me feel more comfortable).
So what are the resources I should leverage to practice API integrations? How should I go about practicing? Especially considering that I do need to perform in a certain way during interviews.
This information is helpful. How do you usually test potential hires? This is a bit interesting because a lot of this I’m unfamiliar with and seems like information that the clients I would work with would implement. Basically, I work with a software company helping others to integrate with our API. That can range from just ensuring they understand what information to expect from certain calls, down to sitting with the customer’s engineers to determining why certain calls aren’t returning information as expected. Regardless, this information is nice to read more about. Thank you
I don’t work at a FAANG, so no leet code or tests. We also don’t have the best pay. Not horrid, but probably 2/3s what a FAANG engineer makes. In addition, I don’t work at a company known for software development. Our primary business is networks and connectivity.
That all said, it can be a pain to find candidates. Our functional programming tech stack is pretty niche to make matters worse just for perspective.
Interviews are typically:
Technical interviews are mostly just talking shop. I have a list of topics and sample questions, but just as conversation starters:
What I’m looking for is someone who understands the technology they work with. Great candidates will relate the question to their experience, not give a text book response. I’ll drill into more nuanced questions if I suspect someone just power studied and doesn’t understand the tech.
For a junior, 10-20% familiarity with the questions is typical. For my level, 70% is ideal. I also don’t ask all of them. If you have 5 years experience with databases I may spend 1-2min with some harder concepts to test the claim and move on.
The more you talk about your knowledge that’s applicable to the role, the more likely my questions will be geared towards your experience.
Personal projects and a public repo will vastly boost your preinterview appearance. I will look at your code, your commit history, tooling you use, etc. This usually tells me more than any interview. I’m not looking for the perfect repo with 100% code coverage, greats docs and comments, etc. I’m looking to see how the code evolved from inception.
I look for contributions to other projects big and small. It tells me you had a problem or needed a feature and had the problem solving skills to make it happen. A big +1.
We also offer APIs which customers integrate against. We don’t want our customers to have to reach out. So in that specific domain I’ll ask about what can be done to avoid those calls. Great docs, FAQ, tutorials, code examples, reference implementations of a client using our APIs, tutorials to build those reference implementations step by step, etc.
Our entire back end has a simulator implementation. Clients get the source. They can test against it locally, look at the source to see what its doing, etc.
We try to provide really good error messages. If a client sends a bad request, we send back exactly where it failed to parse. Clients, through the simulator implementation, can look at the exact parser we use to work it out.
Linux experience is a huge plus. Public dotfiles gives me good insight ahead of the interview.
Personal projects don’t need to be all code. I’ve hired bootcamp programmers who were previously a musician, a baker, and a carpenter. Attention to detail, problem solving, and passion towards achieving a goal are great personality traits.
I ask some pointed questions about AI. I love GPT, but more as a search engine replacement and not an answer book. I have a couple juniors who are really smart, but rely on it way to much. Its output never fits our style guidelines so it stands out. Its vastly hampered their ability to read code. They’ve improved with some interventions, but I try to sus out how dependant a candidate is on it.
Hopefully some of this word soup is of assistance!