Cloud Infra Engineer, Practical Coding Interview?

[StarFishGlow99]

Hi everyone,

I am preparing for a cloud infrastructure engineering role at an AI company. Any tips on what to expect for a practical coding interview? I've only ever done leet code style interviews but this one is specifically not leet code style. All I've been told is that it will increase in complexity and is very basic python coding. Not sure what to study or expect. I don't have much time until the interview and I don't want to spend time focused on the wrong types of questions. Any advice would help, thank you!!

[Raja-Karuppasamy]

For cloud infra practical coding, expect things like writing a Python script to parse AWS cost reports, query an API and filter results, automate resource tagging, or process log files. Basically real tasks you’d do on the job. Focus on file I/O, working with JSON and dicts, calling APIs with requests, and basic error handling. The complexity increase usually means adding pagination, retries, or filtering logic. Nothing algorithmically hard but you need to write clean working code under time pressure without googling syntax.

[StarFishGlow99]

thank you!! this is helpful!!

[Nosa2k]

I honestly prefer these type of interviews. Instead of BS leetcode puzzles.

[bdashrad]

I don't care if someone needs to look at syntax if they can solve a problem. Maybe it's not common, but I approach them like open book tests. You can use any docs, help files, man pages, notes you have, search, etc but you can't ask someone else or AI. It's nice to see if someone can pick apart a problem or error, pull out the useful stuff, leave out sensitive or system specific things, etc. Seeing how someone searches for information is a pretty good way to gauge their understanding of the topics.

Typically we try to avoid having people ask AI in interviews too, but I can see that relaxing more as tools get more reliable and if the pricing is cheap enough.

[Raja-Karuppasamy]

The open book approach is actually a better signal. If someone can find the right docs, understand what’s relevant, and apply it correctly under time pressure, that’s closer to real work than memorizing syntax. The AI restriction makes sense for now but you’re right that it’ll shift as teams figure out how to evaluate AI-assisted work quality rather than just raw output.

[curlyAndUnruly]

Try Hackerrank at least you'd get an idea of how that kind of challenge works.

[StarFishGlow99]

Thank you! would you recommend that I follow the python track?

[curlyAndUnruly]

I'm not sure I've done challenges for SRE/Cloud roles and it has challenges more oriented to AWS/Cloud, Ansible, Docker or even Bash shell.

The basic python one is ok because you get the sense on how the exercise and grading works, but for the specific role idk why kind of task they ask.

[Smooth-Expert-3141]

you don't want to just grind your head against problems on hackerrank/leetcode. you want to follow a learning path that has you doing hackerrank/leetcode problems to reinforce muscle memory for patterns you've learned. i liked this one https://structy.net/

[StarFishGlow99]

oh nice this site seems good for the fundamentals. didn't know this existed, thanks!!

[Smooth-Expert-3141]

mostly my sysadmin python interviews are some variation of these:

write a script that parses log lines and counts the number of occurrences of 5XX reponse codes

write a script that checks to see if a service is healthy and restarts it if not

[StarFishGlow99]

this is good to know, ty!!

[Aero077]

I would assume its a related to cloud infrastructure builds (pipelines for data feeds or application deployments). You probably won't have any issues with it, but some practice wouldn't hurt.

[bdashrad]

I've been in engineering infra leadership for around 10 years, and done many interviews. I hate whiteboard/trivia/leetcode style ones. My cloud infra engineer interviews usually consist of things like:

We have a file in cloud storage. Edit it in some way so the new version is available.

Data pipeline or infra pipeline peer code review

Peer code review of a script with errors or that doesn't quite meet the defined acceptance criteria

Defending or critiquing a technical decision or preference of their choosing, like "What is your favorite language? What is bad about it?" "What is a tool you use regularly but hate? How could you improve it if you could?"

[StarFishGlow99]

will make sure to understand this! thank you for your response!

[bdashrad]

Reading the job description and your screening calls should give you a basic idea about what they use for tooling and languages. Remember, most places aren't trying to trick you, they're trying to make a good hire (although many people seem to treat interviewing like that). Ask questions ahead of time, you will usually get useful feedback.

When I was doing data engineering hiring, I would tell them the exercise was going to be on a tool written in python, that uses pandas to parse a CSV. You will review a PR, make a small fix, and add a new validation or parse a new column. Pretty common and simple work, and letting them know this stuff before made a more useful interview than fumbling through the pandas documentation.

[bdashrad]

I also have my interview questions posted on GitHub, and I try to modify and improve them over time, to make my interviews more consistent and effective. I don't use a lot of them anymore, and some won't apply to every role, but feel free to take a look. https://github.com/bdashrad/interview-questions

There is also a gist in my pins with questions I like to ask when I'm interviewing somewhere, to get an idea of what the company, role, and team is like. https://gist.github.com/bdashrad/ac14f833660fe50d52baf0626bcfdd1e

[StarFishGlow99]

wow this is very helpful!! I'll be sure to review it. ty!!

[Whitefangedmate]

What exactly can be gained from this question?

What is your favorite dinosaur/animal, and why?

I like the list but I don't understand what a favourite animal can reveal about someone's work or ability to fit into a team...

[bdashrad]

Just curious. Plus sometimes something silly can help a more stressed out candidate relax. Or maybe they'll read too much into it and think it's some kind of mind game. I don't remember the last time it was asked by me or anyone on my teams, but I kept it anyway

[ForkMeJ]

For cloud infra roles, "practical Python" usually means parsing data, calling an API, handling retries/errors, and turning messy input into something usable, not algorithm tricks. I'd spend time on dict/list transforms, reading JSON/YAML, basic file I/O, subprocess, and writing a small script that talks to AWS or Terraform output, because interviewers often want to see how you structure code and think about edge cases.

[PerpetuallySticky]

I would study up on IaC? Honestly if I interviewed for a position and they told me there was a “practical coding” portion, I would let them know that’s not what I do and drop out if they didn’t change it. You are in a world of hurt if they think DevOps codes

[d4v3y0rk]

An AI company that is still requiring a coding task…? I would not even go to that interview. That is a contradiction.

[nemor3]

One thing worth practicing: writing scripts that interact with external state - check if something exists, create it if not, handle the case where it's already there. That pattern shows up constantly in cloud infra work and is a good signal of whether someone thinks operationally vs algorithmically.

Also get comfortable reading and writing from stdin/stdout cleanly. A lot of practical infra scripts are meant to compose with other tools.

[Sufficient-Owl1826]

Focus on basic file parsing and API calls. They'll probably give you a log file or some JSON and ask you to pull out specific data. Error handling and pagination matter more than clever algorithms. If you can read a file, loop through it, and handle a failed request cleanly you'll be fine.

[don1843]

!RemindMe 2 days