Updated by Apple candidates
Software Engineer, Cloud Infrastructure (Golang) Interview Experience
The weirdest round was a principal engineer asking me to design an AI bot for ordering employee lunches. I went in expecting cloud infrastructure and Go, then suddenly I'm trying to talk through prompt behavior and architecture without getting lost in the terminology.
Interview process
I got into the process through a referral-like word-of-mouth path after targeting the role myself, and the loop ended up being three stages: a hiring-manager chat, a practical live technical screen, and then a six-interview onsite spread across multiple days because of reschedules. The early rounds felt surprisingly grounded in the real job because I was talking to people from the actual org, not random interviewers from somewhere else in the company. The first technical screen was simple on purpose, just parsing and filtering JSON and then talking through how I'd scale it. The onsite was where the difficulty really jumped, especially the Go-by-hand coding rounds and the AI system design round that caught me off guard. I ended up getting a pretty cold no with almost no feedback beyond that the team didn't find an exact match, which was rough after that much time.
- Phone interview
- Technical interview
- Final round
Interview tips
I'd know my projects cold, but not in a memorize-the-bullets way. I'd be ready to explain the business context, the architecture, the conflicts, and the scale of impact, because that opened up way better conversations for me than just listing tasks. For Apple specifically, I'd assume you need to hand-write code and, if the role is Go-heavy, I'd prep in Go even if someone tells you a round might be language agnostic. I'd also keep the kinds of roles I'm interviewing for pretty tight, because too much context switching kills your prep fast. And I'd keep pushing for clarity when the process details sound fuzzy instead of assuming the recruiter has it all perfectly lined up.
Company culture
I saw a pretty clear hiring-manager-first trend in this process, which I hadn't really seen as much earlier in my career. I actually get why they're doing it, because that chemistry check happens early with someone who probably has a major vote. The interviews themselves felt warm and very team-specific, which I appreciated, because I was mostly meeting people I'd actually work with. The recruiting side felt a lot more overloaded and inconsistent, especially around details like whether a round was language agnostic. I also would not count on any AI coding help there. From what I heard and from how the loop ran, they want you writing code by hand.
Questions asked
Overview
The onsite was the real grind: six interviews spread across multiple days because of reschedules, a noticeable jump in difficulty, and very clear expectations that I would hand-write Go for the coding rounds.
Question types asked
Specific questions asked
Build a Go implementation to manage requests within a certain time span.
How will you track requests that become obsolete?
What functions would you add on top of the base implementation?
What assumptions do you need to make for parts that are out of scope?
I had to build a Go class-like implementation around managing requests inside a time window. The tricky part was keeping track of active versus obsolete requests and continuously dumping anything that fell outside the window while still building the required functions on top. It was algorithmic, but there was a lot of abstraction, so I spent most of the hour talking through assumptions and possible approaches with the interviewer instead of silently coding. I proposed the class structure myself and focused on satisfying the core requirements first.
Write a Go function to maintain a string as bytes.
How would you handle the state management cleanly?
Can you also talk through your understanding of infrastructure as code for this role?
The first half was a coding question about maintaining a string in byte form, and the main difficulty there was the state management. Once we got through the ambiguity, it was still a normal coding problem, and the interviewer gave pretty generous hints. The second half shifted into infrastructure as code, which made sense for the role. I talked through the concepts and technologies I knew and treated it almost like a mini design discussion around internal platform tooling and how I'd think about codifying infrastructure.
What are the functional and non-functional requirements?
How would you model the cluster in the system?
This was with the hiring manager again. I got a little tripped up early because I wasn't immediately treating the Kubernetes cluster itself as a piece of data, so I bounced around between functional and non-functional requirements longer than I wanted. Once that clicked, I could work through the architecture and diagram the system. He let me think out loud and write notes rather than forcing everything into a rigid drawing flow, which helped because the diagramming tool was honestly slowing me down.
Tell me about a time, as a customer, when you had a great customer experience.
How do you work through conflict on teams?
This round was with another engineering manager in the org and stayed very behavioral. On the disagreement and team-conflict side, I walked through how I handle friction without letting it derail the work. The most unique question was about a great customer experience I had personally. I used a garage service example where the product made troubleshooting at home really efficient and clear. I took that as them testing what I actually recognize as good customer experience, not just whether I had a polished canned story.
How should the AI components behave?
How would you structure the workflow and architecture?
How would prompt behavior fit into the system?
This was the round where I struggled the most. A principal engineer asked me to design an AI lunch-ordering bot, and I came in expecting cloud infrastructure, not that kind of question. He was using a lot of AI and LLM terminology up front, and I got a little intimidated because I started thinking at the wrong level of abstraction. He gave me a lot of context, and once I adjusted, I got to a solution he agreed with. It was more about workflow, prompt behavior, and how the pieces fit together than about evaluation metrics.
Tell me about a bug you solved and the impact it had.
How do you handle conflicts and work on teams?
This was with the product manager, and it was labeled behavioral but definitely had product-sense mixed in. When she asked what I'd improve about any Apple product, I first assumed she meant something inside the org, so I had to reset and think broader. We also talked about a bug I had fixed and the impact it had, plus the usual teamwork and conflict questions. She was very passionate and set a strong tone, and I was able to match her energy, but it was definitely broader than I expected for a software loop.
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