Meta Software Engineer Interview Guide

The Meta Software Engineer interview loop typically goes through these stages:

1. Recruiter screen (or written prescreen form for some roles)
2. Online assessment (some E3-E5 loops)
3. Initial tech screen (a longer structured screen at E6)
4. Full loop, 4-6 interviews:
   Coding (2 rounds)
   AI-enabled coding interview (usually 1, and the only coding round at E7 and above)
   Design Interview (none at E3, 1 at E4 & E5, 2 at E6+)
   Behavioral Interview
   Project retrospective (some E6+ loops, out of scope for this guide)
5. Hiring committee and team match

If you’re interviewing for the Software Engineer, Machine Learning track, please refer to our Meta MLE interview guide. 

This is a 30 minute call on which you'll talk to your recruiter about your

• background
• experience
• long-term goals 
• why Meta 

and other relevant details so they can lock in a level that sets the bar for how you’ll be evaluated for the rest of the loop.

They'll also ask you about your areas of expertise and a few questions on how you've addressed technical challenges in some of your previous projects.

For some roles, Meta replaces this call with a written prescreen that has questions like:

• What AI tools do you use every day for engineering work?
• Have you worked on projects where AI was central to the architecture? How did you make sure you designed responsibly?
• How do you assess the quality and reliability of AI output? 

Use this call to settle the details of the interview like your choice of coding language and variation of design rounds between Systems Design or Product Architectural design. The design rounds are typically picked by the recruiter based on your experience and role. And of course, if the AI-enabled round applies to you. 

Establish a good rapport with your recruiter by being upfront about your background and what you want out of your career. Meta recruiters are pretty much famous for advocating for candidates they like later in the process, so they're good people to have on your side. 

We also recommend that you try and deflect any comp questions because your final level will be decided at the end of the interview loop by the hiring committee and comp will be decided accordingly.

Some E3-E5 loops add a 90-minute proctored CodeSignal assessment that you’ll take with your camera and mic on. If it applies to you, the result will be read along with your performance in the tech screen. 

The assessment is 1 problem split into 4 levels. Each level will unlock and reveal its requirements only after you’ve passed the previous one. You can only read the unit tests that grade your code, you can't edit them. To debug, you can write print statements in a separate scratch file and run them there. 

You can open tabs for language syntax should you need it. You can’t search for solutions (obviously) or use AI. 

Expect questions like:

• Build a cloud file storage service. 
• Implement a banking system (features get added as you progress in levels)

Some candidates also get a work-style assessment to complete at this stage. 

This is a 45-minute technical screen with an engineer where you’ll solve 2 algorithmic coding problems in a collaborative editor like CoderPad. This round is the gatekeeper to the onsite loop. 

The problems are typically medium-difficulty LeetCode style questions that’ll test CS fundamentals like DSA and binary trees. You’re expected to talk through your logic, write clean code while discussing time and space complexities. 

If you’re an E6 candidate, this screen is usually replaced by a 60-min Structural Screen where roughly half the time is cordoned off for behavioral questions. At this point, the screen exists to decide if you stay in the run for E6 or get downleveled to E5 when you appear for the onsite rounds.

More recently, since mid-2026, some E5+ candidates who filled out the prescreen form sat through a 60-minute AI-native Screener in place of this screen. It features a standard coding problem but also has questions about how the candidate has been using AI in their projects with a couple of behavioral ones too. 

The 4 official focus areas scored here are the same ones listed for the onsite Coding rounds.

Expect questions like:

• Decide if a string can become a palindrome after deleting at most one character.
• Find the kth largest element in an unsorted array.
• Count the 1s in a subarray of a large binary array, given its start and end indices.
• Compute the dot product of 2 sparse vectors.

There are 2 things to remember when you sit down for this round:

• Present more than one approach to the problem you’ve been given and clarify on which one to pursue with your interviewer before you code. If you’ve seen/solved it before, Meta expects you to tell your interviewer so. To be fully prepared for this round, we suggest that you practice medium and hard problems and aim to solve them in under 15 minutes each. 
• A non optimal solution that works is always a better result than an optimal idea that has nothing working for it. 

For the onsite, you’ll face 4-6 rounds that’ll cover

• Coding (with the possibility of the AI-enabled version)
• Design
• Behavioral
• And maybe a Project retrospective if you’re E6 or above 

with the exact rounds and number depending on the level you’re targeting. 

We don’t cover a separate section on the retro but should your recruiter slot it in your loop, we suggest that you choose a project that:

• Is large in scope and has measurable impact
• Has strong technical decisions you are responsible for
• Has well thought-out tradeoffs that you can defend
• Has clear, defined success metrics that have been measured
• Is a good example of your ability to collaborate with cross functional partners like DSs, PMs, UXRs. It’s important that you worked across teams without relying on your rank/ title and were able to get their buy-in reasonably with data and interpersonal skills 

This is a 45-minute round conducted on CoderPad that tests your speed, accuracy and the quality of your problem-solving under a strict time limit. Typically, you’re expected to solve 2 DSA questions of LeetCode medium to hard difficulty that need dry-running on your end because the interviewer won’t compile your code. 

Minor syntax errors are forgiven and you can write in any language you're comfortable with, though our coaches say it’s just easier to go with scripting ones. 

The 4 official focus areas for coding are: 

• Problem Solving: the quality of your reasoning behind a solution, developing and comparing more than one, and choosing the appropriate data structures and algos and speaking to space and time complexity on the way to optimizing.
• Coding: Assesses if you can convert solutions into executable code and if the code is organized and captures the right logical structure.
• Verification: this is a check on if you're considering a reasonable number of test cases or coming up with a good argument for why your code is correct. This aspect is pretty important because you’re expected to manually trace edge cases and you don’t have the luxury of a compiler or autocomplete. The official Meta guide that we mentioned earlier states very clearly that catching a bug is good news (and even uses an exclamation point). 
• Communication: This is a fairly direct assessment of if you're asking the right questions about reqs and keeping the interviewer in the loop about your approach. 

The traditional coding round focuses heavily on volume and pattern recognition where recent loops report the occasional problem can be solved with recursion + memoization. Meta states in their PDF that they don’t ask DP questions, though. 

Expect questions like:

• Remove the minimum number of parentheses needed to make a string valid.
• Return the vertical order traversal of a binary tree, column by column from left to right.
• Evaluate an arithmetic expression string that contains +, -, * and /.
• Check if a word matches an abbreviation that replaces runs of letters with their count.
• Find the LCA of 2 nodes in a binary tree.

Expect a few follow-ups once you’ve solved the problem. They could ask you to solve it again under a tighter time/ space limit or build on it by asking you questions like how your solution would behave when the input grows 10x, for example.

In most SWE loops, this round replaces 1 of the 2 coding rounds and at E7+, this is the only version that’s applicable. You’ll sit down for a 60-minute interview with a Meta engineer and a multi-file project and use an integrated AI assistant in CoderPad to build and optimize code instead of solving LeetCode puzzles from scratch. The pad will have 3 panels: a file explorer, editor and AI-chat panel.

The interviewer will begin by orienting you about the environment and files. After that, you’re expected to go through the following 3 phases:

• Code Understanding: You’ll explore the unfamiliar codebase and run a couple of initial tests to analyze existing classes or functions to find your footing. 
• Bug Fixing/Code Implementation: Tactfully fix broken implementations, fill in missing logic, add new features and whatever else the task/interviewer asks of you.
• Implementation/ Optimization: Handle edge cases or switch algorithms entirely (e.g., moving from a greedy approach to a trie or optimized search).

Expect questions like:

• Fix a maze solver in the codebase given to you so that it prints the path it finds. Then, extend it to support new cell types like portals or locked doors.
• From a given list of words, choose the subset that maximizes the number of unique characters without going over a total character count

While you’re still judged on the traditional competencies mentioned under the Coding round, there are certain additional nuances:

• You have to take the lead in this round and resist the urge to write out broad/non-directional prompts like “find all the bugs”. You’re being evaluated on your judgment and ability to direct the AI so treat it like a junior engineer and be sure to validate its output. 
• Specifically about code verification, the AI models provided can hallucinate or miss edge cases so you should review and test methodically. Candidates report that the assistant’s performance is pretty bad (purposely) so be ready to work out the algorithm yourself. 
• Over-communicate in this round. Vocalize your thought process all the way through, especially about why you’ve structured your prompt a certain way, what results you expect, how the AI is meeting/slipping that standard and what tradeoffs are involved in the entire ordeal. 

Second only to Design, this round sees the highest volume of practice bookings on our platform, especially in the recent past. We went through the full transcript of a Staff-level mock interview for the AI-enabled coding round (with permission, of course) for some tips for you:

This round is a 45-minute collaborative discussion where you'll architect a large-scale system or user-facing product by starting off with an open-ended prompt. The interviewer will introduce new data/ constraints partway and you’ll have to talk through how you scale up to the level Meta needs, alongside what that might mean for success and failure scenarios.

Depending on your role and team track, the interview will take any one direction:

1. System Design: You’ll focus on distributed systems and discuss the 8 official areas Meta expects: testability, usability, extensibility, security, portability, availability, scalability and operational characteristics. Expect this version if you’re interviewing for an infra role. 
2. Product Architectural Design: This version is more focused on API design, usability and utility. As an engineer interviewing for a Product role, you’ll touch upon storage data models, scalability, design patterns, data ownership, protocols, data formats, client-server design, designing for long-term vs. complexity, and accommodating possible product changes.

We cover both system and product design rounds in depth in our Meta EM guide. Even though it’s framed around high-level expectations, the core structure and principles apply directly.

The official focus areas that you’re going to be assessed within the design round are: 

• Problem navigation: How well you organize the problem space and its constraints by asking the right clarifying questions to winnow down the ambiguity till you have a clear set of reqs to design to
• Solution design: You produce a working design for the whole problem (or pieces of it) by choosing the right components and explaining their interactions. It’s important you don’t lose sight of the big picture/ what you’re originally meant to accomplish. 
• Technical Excellence: Your nuance in handling trade-offs, consistency models, scale constraints, etc. 
• Technical communication: You explain your vision and reasoning clearly and respond well to hints/ redirection from the interviewer because at the end of the day, Meta frames this round as a peer-peer conversation and it should be treated as such. 

Recently, Prepfully candidates reported facing the following prompts:

• Design an ad-click aggregator
• Architect a world-wide video distribution system.
• Design a distributed cache like Memcached.

This is a 45-minute conversation with a Meta engineer or EM about your past work and together with the Design round, your performance here sets your level. Expect 4-5 questions with follow-ups. 

At senior levels and above, this round can carry more weight in leveling than its 45 minutes suggest. Austen McDonald, ex-Meta hiring committee member, says “the first thing I would do is go to the behavioral interview in a senior candidate’s packet”. 

Your interviewers will want to learn about your background, what you’re passionate about in tech, what kind of impact you wish to make and how Meta is the right next step for all of these. 

Expect questions like:

• How do you use AI to increase your engineering productivity?
• Have you ever hurt a working relationship because of a conflict? Did it recover?
• What project are you most proud of? 

Since mid-2026, SWE behavioral rounds are reported to score these 5 updated signals:

• AI Driven impact
• Continuous AI-learning
• Partnering 
• Embracing Ambiguity
• Communicating Effectively 

To have an anecdote for every type of scenario or follow up, we suggest that you make a story bank. Make sure you have stories about:

• Operating in ambiguous projects/ taking the lead on undefined ones
• Moving quickly while showing resourcefulness and a bias for action
• Transparency on failures and what you learnt from them
• Building relationships with direct and partnering teammates to work together 
• Convincing/ getting buy-in from peers who initially resisted your goals/ plans
• Self-awareness and introspection wrt your professional growth and personal impact thus far

Most importantly, have a story about using AI at work where you can state the result and explain what you checked in the AI’s output. Meta's current Software Engineer, Product postings list measurable impact from AI tools as a preferred qualification. 

We recommend that you take the classic STAR framework and build it out into STAR+ (Situation, Task, Action, Result + the X-Factor: Learning) to structure your stories. The X-Factor at the end - Learning - is your definitive chance to demonstrate intellectual humility, and helps you reflect on a personal takeaway on how that situation changed you for the better. Be honest and open about the learning, even if it went south. Meta values honesty and appreciates you learning from such situations. 

At the end of each round, interviewers get 24 hours to submit their notes and choose from Strong Hire, Hire, Leaning No Hire, or No Hire for you. 

The Hiring Committee, consisting of senior SWEs, then reviews that feedback to make the final call and decide your level. 

If the committee signs off on a “yes”, you’ll then move into the Team Matching phase where you'll do 30-minute informal chats with HMs until you zero in on a fit.

• E3: $181K
• E4: $308K
• E5: $434K
• E6: $707K

View Meta SWE compensation data on Levels.fyi