I interviewed for Meta’s Production Engineer role recently, and the prep that actually mattered was much narrower than people think. Fundamentals get tested directly, and anything outside that didn’t show up.

For the technical rounds, almost everything leaned on Linux internals (processes, cgroups, namespaces, signals), debugging tools like strace, tcpdump, lsof, basic networking (TCP handshake, DNS resolution, routing), and figuring out why a service is unhealthy using logs, metrics, and resource symptoms. Practicing this hands-on made a much bigger difference than reading theory.

Coding wasn’t Prepare.sh-hard. I got problems like parsing structured logs, merging config files, scanning huge strings efficiently, and simulating small system behaviors. Clean code, no bugs, and good test cases mattered more than clever algorithms, but you still need solid arrays, maps, stacks, and string manipulation.

The interview loop was:
(1) PE fundamentals,
(2) coding,
(3) systems/OS deep dive,
(4) behavioral tied to Meta's values (e.g., “move fast,” “focus on impact,” “be open”).
Timed mocks helped me get used to explaining decisions out loud and working with incomplete or misleading information — they purposely don’t give you the full picture.

For behavioral, I prepared 6–8 STAR stories around owning real outages, debugging multi-team issues, deploys gone wrong, mistakes I learned from, and projects where I unblocked others. I reused the same stories but adjusted the angle: sometimes focusing on urgency, sometimes on collaboration, sometimes on tradeoffs under pressure.

You generally should not over-optimize for tool-specific questions like Kubernetes, Docker, or particular cloud vendors for a Meta Production Engineer interview. Instead, the focus is usually on timeless fundamentals that transfer across any stack.

What not to over-focus on

Spending lots of time memorizing Kubernetes YAML, Docker flags, or specific CI/CD tools is rarely the best use of prep time at this stage. These tools change frequently, and interviewers care more about whether you understand how systems work than which buttons you know how to press.

What to expect technically

Expect Linux fundamentals questions: processes, signals, filesystems, permissions, system resource usage, and how to debug issues using core CLI tools. You will likely see scripting in Bash or a similar language, often around log parsing, automation, or simple data processing, plus light data structures and algorithms that test clarity and correctness more than advanced theory.

Networking is critical

Networking should be prepared exceptionally well: understand OSI/TCP/IP basics, routing, DNS, load balancing, firewalls, and how to debug latency, timeouts, and connection failures. Be ready to reason through real-world scenarios like “site is slow for some users,” “service cannot reach a dependency,” or “packet loss in a specific region,” and to explain the concrete steps and tools you would use to investigate.