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Meta Software Engineer Interview Guide

Built directly on Meta’s interview evaluation criteria, with a detailed stage by stage breakdown of the SWE interview process and the types of questions assessed at each step

Updated: 19 Feb 20269 min read21973 readers

This guide is not speculative, crowdsourced, or even mildly unsure.

It is informed directly by Prepfully coaches who are Senior EMs, Staff Engineers and even one Senior Staff Engineer at Meta right now. They sit on hiring committees, sharing verbatim how candidates are evaluated and that is paired with insight from candidates who recently cleared the interviews, living the experience end-to-end.

This guide is written by people who hire and people who just got hired, to make it easier for you to take your place amongst them.

For insights into similar roles, review the guides for Meta Frontend Engineer.

Meta Software Engineer Interview Process Explained: Rounds, Evaluation Criteria, and What Meta Looks For

Round/ Format/ Time

Core Fundamentals

What Meta Is Evaluating

Recruiter Screening Virtual · 30–45 min

• Abstract past work into problems, constraints, scale, and outcomes.
• Explain how systems connect to product and business goals.
• Show understanding of ownership, scope, and team boundaries.
• Demonstrate baseline architectural and technical literacy.
• Articulate level expectations and career progression.

• Clear ownership versus team contribution
• Structured, intentional communication
• Motivation aligned with Meta’s product and engineering problems
• Career trajectory and level alignment

Initial Screening
Virtual · 45–60 min ·
CoderPad

• Strong grasp of arrays, strings, hash maps, trees, and recursion.
• Decompose problems before coding.
• Use time and space complexity to guide solutions.
• Write readable, correct code without execution.
• Validate through examples, edge cases, and pattern recognition.
• Adapt approach as constraints evolve.

• Problem solving approach over speed
• Continuous narration of thought process
• Code structure and logical flow
• Self debugging and bug fixing
• Asking clarifying questions early • Comfort adjusting approach mid-solution

Technical Skills
Onsite · 45 min

• Advanced use of trees, graphs, stacks, queues, recursion, and iteration.

• Generate and compare multiple solution strategies.
• Translate abstract problems into concrete algorithms.
• Write structured, maintainable, production minded code.
• Prove correctness beyond samples and handle edge cases.
• Maintain coherence under pressure and changing constraints.

•Communication consistency
• Depth of problem solving reasoning
• Coding quality under pressure • Verification discipline
• Engineering maturity
• Ability to explain decisions clearly
• Willingness to revise and refine
• Signal consistency across interviews

AI-assisted Coding
Onsite · 45 min

• Strong grounding in core data structures and algorithms, independent of tooling
• Ability to read, understand, and critique generated code • Translating problem requirements into precise prompts or instructions
• Reasoning about correctness, edge cases, and failure scenarios
• Debugging and refactoring code written by someone else (or something else, in this case?)
• Understanding time and space complexity even when code is generated
• Maintaining code structure, readability, and intent while iterating

• Clear problem solving reasoning, especially when you're being assisted by an LLM
• Ability to verify and validate outputs instead of trusting them blindly
• Judgment in deciding when AI output is helpful and when it needs correction
• Communication of intent, assumptions, and trade offs while using assistance
• Ownership of the final solution, regardless of how it was produced
• Comfort iterating, refining, and steering solutions toward correctness
• Awareness of limitations, edge cases, and unintended behavior
• Maintaining engineering rigor while moving faster
• Signal that you can work effectively in a modern Meta codebase where AI tooling exists
• Meta is NOT evaluating how you prompt AI

System Design and Product Architecture
Onsite · 45 min

• Distributed systems principles
• Data partitioning and replication
• Consistency and availability trade offs • Caching and performance optimization
• API and interface design
• Data modeling for access patterns
• Failure modes and recovery strategies • Scalability planning
• Extensibility and maintainability
• Observability and operability
• Security and testability

• Problem navigation in ambiguous spaces
• End-to-end solution design
• Technical excellence in decision making
• Explicit trade off articulation
• Structured technical communication
• Scalability thinking • Availability awareness
• Extensibility mindset
• Security consciousness
• Testability awareness
• Operational thinking

Behavioral / Leadership Round Onsite · 45 min

• Decision making under constraints
• Handling incomplete information
• Technical and interpersonal risk management
• Prioritization and trade offs
• Measuring success and impact
• Learning from failure
• Applying feedback over timeInfluencing without authority
• Long-term judgment development
• Structured reflection

• Ownership
• Resolving conflict
• Embracing ambiguity
• Driving results
• Growing continuously
• Communication effectiveness
• Self awareness
• Accountability
• Adaptability
• Decision quality
• Impact orientation
• Learning mindset
• Behavioral consistency

Meta Software Engineer Levels Explained: Scope of Work, Expectations, and Hiring Signals by Level

Level

Scope of work discussed in interviews

Signals interviewers listen for

E3 (Software Engineer)

Well-scoped tasks, individual features, bounded problem statements, local code ownership, execution within clearly defined requirements

Strong CS fundamentals, correct use of data structures and algorithms, ability to follow direction, asking clarifying questions, clear communication, learning velocity, growing continuously

E4 (Software Engineer)

End-to-end feature ownership, moderate ambiguity, interaction across components, basic design decisions, handling edge cases, impact beyond a single module

Solid problem solving, clean and maintainable code, ownership of outcomes, comfort with some ambiguity, sensible trade offs, verification discipline, driving results within assigned scope

E5 (Senior Software Engineer)

Large features and subsystems, loosely defined requirements, cross-component design, scalability and performance considerations, longer-lived systems, expanding ownership over time

Strong technical judgment, system-level thinking, embracing ambiguity, balancing velocity with long-term health, resolving conflict in design discussions, influencing peers, repeatable execution patterns, consistent driving of results

E6 (Staff Software Engineer)

Multi-system architecture, broad and ambiguous problem spaces, unclear problem boundaries, long-term technical investments, cross-team and cross-org dependencies, operational responsibility

Problem navigation across ambiguity, technical leadership without authority, deep trade off analysis, scalability and availability reasoning, anticipating risk before it surfaces, balancing short- and long-term impact, org-level ownership, influencing decision making beyond immediate team

E7 (Senior Staff / Principal Engineer)

Org-wide or company-wide systems, highly ambiguous problem statements, platform and infrastructure evolution, foundational technical bets, multi-quarter and multi-year scope

Setting technical direction, managing complexity across systems, anticipating failure modes early, operating effectively amid strong opinions, product sensitivity in technical decisions, mentoring senior engineers, sustained and repeatable impact at scale

Recruiter Phone Screen

This is the first round of the interview process and it usually takes the form of an informal phone or video call with a Meta recruiter. Nothing technical happens here, but the conversation still matters, because this is where Meta builds an early picture of your background, motivation, and trajectory.

You can expect questions like:

  • Walk me through your background and the work you have been doing recently.
  • What interested you in this role, and what about Meta feels like a good next step for you?
  • What kinds of problems or projects have you enjoyed working on the most, and why?
  • Tell me about a project that challenged you in a meaningful way and how you approached it.
  • What are you hoping to grow into over the next few years, and what kind of team or work environment helps you do your best work?

This is also the stage where the recruiter may mention Meta’s accommodations process more broadly, just to make it clear that support is available if you need it. The goal is for every candidate to be able to play to their strengths on equal footing once the technical rounds begin.

Also, take a moment to communicate to your recruiter how serious you are about this role. Once a Meta recruiter decides you might be a strong fit, they really show up for you. They are surprisingly generous with context, timelines, and guidance in a way that makes the process feel far less opaque than people expect.

Initial Round (Technical Phone Screen)

This round is a 45-minute technical interview conducted over Zoom using a shared editor (currently CoderPad), and it is designed to assess your core coding fundamentals before moving you into the full loop.

Our coaches inside Meta hiring for this role have told us that you will be evaluated on exactly these parameters: problem solving, coding, verification and communication

Code is not executed, minor syntax issues are fine and Prepfully candidates who recently cracked this interview mentioned that Meta treats finding and fixing your own bugs as a positive signal.


What happens in this round:

  • Short introductions and light context setting
  • 35 minutes focussed on one or two coding problems on algorithms and data structures (almost always typically medium LC level)
  • Coding in a plain text environment without execution, autocomplete, or debugging tools
  • An expectation of you to have an ongoing discussion on requirements, solution options, and trade offs
  • A few minutes at the end for your questions (one of the easiest moments to leave a memorable impression)


Interview questions in this round:

  • Write a code to check whether a given string is a palindrome or not
  • Given an integer array, return an array such that the value in the array is the product of all values of the original array except the number in that position in the original array.
  • Print a binary tree in a zigzag order.
  • Write a code to find all nodes in a binary tree at a distance of N from the leaf nodes.
  • Given the root of a binary tree, determine the number of root-to-leaf paths such that the sum of the values of the nodes is N.
  • Determine whether a given string matches a pattern that may include wildcard characters (wildcard pattern matching problems have shown up a couple of times for a few candidates)

You can code in the language you know best. DON'T write in pseudocode. If your performance sits too close to the cutoff, Meta may add one more technical interview to round out the decision.

Onsite Rounds

The interviewer is not invested in your growth, they are there to score what shows up in that hour. You can learn from a mistake with a coach; you can’t argue with an interview score, so pick where you mess up.

See the difference a Meta SWE Mock Interview Coach can make

Coding Interview

Meta turns the dial up from the initial screen by expecting more depth, structure, and consistency in how you think and code. The interview runs for 45 minutes, with most of the time spent solving one or two coding problems and the rest reserved for discussion.

Prepfully’s Mock Interview Coaches in Meta tell us that in this round, the evaluation criteria are problem solving reasoning, code organization, verification logic and communication skills as fundamental evaluation.

Interviewers can only assess what you show during the interview, which is why talking through your thought process, trade offs, and decisions out loud is expected rather than optional. Prepfully’s candidates who recently interviewed said the round worked in their favour when they treated it like a working session rather than a silent test.

You can hope the pressure does not get to you, or you can meet it early.

Over 2873 candidates chose to rehearse this exact round and they would strongly suggest you do not walk in blind.

Prepare with a Prepfully Meta SWE mock interview coach for the real feel.

What happens in this round

  • Brief introductions and context setting
  • One or two coding problems with more depth than the phone screen
  • Coding in a plain text environment without execution, autocomplete, or debugging tools
  • Ongoing discussion of requirements, assumptions, and trade offs
  • Explicit attention to code structure, space and time complexity, and verification
  • Occasional light tie-ins to your past experience or how you’ve solved similar problems in real systems


Interview questions:

  • Find the length of the longest subarray that contains at most k distinct elements
  • Detect whether a cycle exists in a graph and return the cycle if one is found
  • Design a data structure that supports streaming integers and can return the median at any time
  • Determine the length of the longest substring without repeating characters
  • Find the lowest common ancestor of two nodes in a binary tree

AI-enabled coding interview

In October 2025, Meta began piloting an AI-enabled coding interview that replaces one of the two coding rounds at the onsite stage. It’s 60 minutes in a specialized CoderPad environment with an AI assistant built in. It’s highly likely that this round will be rolled out for all back-end and ops-focused roles in 2026.

This is what the average experience looks like:

If you’d like to know more about this round, head to the AI Assisted Coding Round deep dive

System Design and Product Architecture

This round is a 45-minute design interview and, depending on the role, it will focus either on System Design or Product Architecture, a distinction Meta calls out explicitly. System Design interviews lean toward distributed systems, scalability, performance, and efficiency, while Product Architecture interviews focus more on API design, client-server interactions, usability, and how products evolve over time, but in both cases the goal is the same: to see how you solve a non-trivial, open-ended engineering problem.

Here, you will be judged upon four core criteria: Problem navigation, solution design, technical excellence, technical communication.

Here’s exactly how this round unfolds in the Meta Software Engineer interview:

  • A brief introduction and framing of the session, including whether the interview will focus on System Design or Product Architectural Design
  • A high-level, non-trivial design problem with intentionally incomplete information, where you are expected to drive the conversation rather than wait for instructions
  • Early problem navigation, including organizing the problem space, asking clarifying questions, identifying constraints, and defining a clear set of requirements to design against
  • Discussion and construction of a working solution, either at the system level or product level, with an emphasis on connecting multiple concepts into a coherent design
  • Ongoing evaluation of solution design, including how well your approach addresses the full scope of the problem rather than isolated components
  • Deeper technical dives when appropriate, to demonstrate technical excellence, including dependencies, trade offs, and risk mitigation
  • Explicit reasoning through Meta’s core technical dimensions: scalability, availability, extensibility, security, testability, usability, portability, and operational characteristics
  • Clear and structured technical communication, with interviewers paying close attention to how well you articulate your ideas, respond to feedback, and adjust your design as new considerations emerge
  • Use of diagrams to make ideas concrete and collaborative using Excalidraw
  • Consideration of failure modes, bottlenecks, and how the system or product would be diagnosed or debugged in real operation
  • Time at the end for your questions, often opening space for discussion about how similar systems are built and evolved inside Meta


Here are some recently asked Meta SWE System Design Interview Questions. To see where you stand, you can also input your answers into the free answer reviewing tool and evaluate your answer against Meta's rubrics.


See the most recent System Design questions in the Meta SWE interview, reported by recent candidates for free.

For new grad or junior Software Engineer roles at Meta, system design is usually not its own standalone round. The interview loop leans much more heavily toward coding, data structures, and algorithms.

That said, you are not completely off the hook. You might still see lighter, more foundational system design or product design style questions that check whether you understand APIs, basic data modeling, and how client server systems work together.

Behavioral Interview

The Behavioral Interview is a 45-minute interview in Meta’s onsite loop and it is a structured evaluation, not a free-flowing chat, even though it may feel more conversational on the surface.

Prepfully experts who work inside Meta (and sit on hiring committees) have been refreshingly direct about this round. There is a clear scorecard, and the evaluation criteria come down to these categories: resolving conflict, growing continuously, embracing ambiguity, driving results, and communicating effectively.

Interviewers will ask you to anchor your answers in specific past experiences, so guide the conversation deliberately.

We recommend moving beyond STAR now (which has been the popular framework for these interviews for the last decade or so); and instead move to use CAR (Context, Action, Result) for two reasons
(a) it's more concise, and time is precious when you're trying to demonstrate your years of awesomeness in 45min
(b) it's what Meta's started using internally to assess interviews (yep, you heard it on Prepfully first).

Vague, abstract, or hypothetical answers are usually redirected, so every story should be concrete, scoped, and outcome driven, especially now that you understand exactly how those stories are evaluated.

What happens in the Behavioral Round and what your interviewer is gathering about you:

  • Questions about specific projects, challenges, or decisions you were directly responsible for. They are often centered on a challenge where you were responsible for both the approach and the outcome. You will be asked to explain how you thought through the problem, what options you considered, and why you went the way you did. Influence matters too, especially how your thinking changed the direction of the work or helped others align.
  • Follow ups that dig into your problem solving reasoning, where interviewers want to know why you picked that approach, what constraints shaped it, and whether you considered alternatives before locking in a solution
  • Examples that show how you embraced ambiguity, like moving forward when requirements were incomplete, priorities were still settling, or the problem itself was not fully understood yet, and how you reduced uncertainty through iteration rather than waiting for perfect information
  • Exploration of conflict and disagreement, where interviewers look at how you worked through differences with teammates or partners, how you listened to other perspectives, and how you reached alignment
  • Clear articulation of how you drove results, focusing on what changed because of your work, how success was defined upfront or refined along the way, and how you knew the solution was doing what it was supposed to do once it was in use
  • Reflection that shows growing continuously, where feedback from peers or downstream teams forced a rethink, and you can clearly explain what you do differently today because of it, not just what you learned in theory

Interview questions:

  • Tell me about a time you had to adapt to a significant change or a new process.
  • Elaborate on a decision you made that was unpopular at the time but you still stand by.
  • Describe a project where the technical solution was sound but the outcome still fell short. What did you learn from that?
  • Tell me about a time you identified a risk that others did not see at first. What happened?
  • Tell me about a project where your role evolved significantly over time. How did you adapt?
  • Describe a time you had to make a call that had real consequences and limited opportunity to reverse it.

Offer and negotiation

Offers at Meta are level driven and heavily weighted toward equity, so the most important negotiation work happens earlier, when your impact and trajectory are being calibrated.

When compensation comes up, Meta expects a calm, well-informed conversation, where you advocate for yourself thoughtfully and with context. For role, level, and location-specific details, head to Levels.fyi

Recently reported Meta Software Engineer interview questions

Develop a service for managing distributed job queues.

System Design

Design a system for managing secrets in a distributed environment.

System Design

Build a data lake management system for distributed infrastructures.

System Design

Frequently Asked Questions