Meta Backend Engineer Interview Questions (2026)

1. 1Recruiter screen30 minEasy

   Process overview, level calibration, and prep guidance — Meta recruiters actively coach on round formats.

2. 2Technical screen45 minHard

   Two DSA problems in 45 minutes on a plain shared editor with no autocomplete or execution.

3. 3Coding round ('Ninja')45 minHard

   Two more problems at loop difficulty; clean near-compilable code and verbalized complexity analysis expected.

4. 4System design ('Pirate')45 minHard

   Design a Meta-scale product system (feed, Stories, chat) with emphasis on read-heavy fan-out, caching, and data modeling.

5. 5Behavioral ('Jedi')45 minMedium

   Deep past-experience discussion on conflict, growth, and impact aligned to Meta values; graded as a real signal round.

1. Q1

   In a Meta product/system design round, answer this: Design an experimentation platform for WhatsApp

   HardHigh Level DesignA/B testing platform

   How to answer:

   Use deterministic assignment, experiment config service, exposure logging, metrics pipeline, guardrails, and analysis dashboards; handle mutually exclusive experiments. Discuss read-heavy fanout, ranking, privacy, and product trade-offs.

2. Q2

   In a practical product design drill, answer this: Design a reusable API client for Reels with auth refresh and request signing

   MediumLow Level DesignAPI client with auth

   How to answer:

   Separate HttpClient, AuthProvider, TokenStore, RequestSigner, RetryPolicy, and Serializer; refresh tokens safely and avoid logging secrets. Optimize for simple, scalable product objects and fast iteration.

3. Q3

   In a Meta product/system design round, answer this: Design an API gateway for Instagram Stories backend services

   MediumHigh Level DesignAPI gateway

   How to answer:

   Handle auth, routing, rate limits, request validation, retries/timeouts, observability, and versioning. Keep business logic out of the gateway. Discuss read-heavy fanout, ranking, privacy, and product trade-offs.

4. Q4

   In a Meta product/system design round, answer this: Design an ad-serving system for Groups

   HardHigh Level DesignAd serving

   How to answer:

   Separate request routing, candidate retrieval, auction/ranking, budget pacing, frequency capping, logging, and fraud detection; optimize p99 latency. Discuss read-heavy fanout, ranking, privacy, and product trade-offs.

5. Q5

   In a Getting-to-Know-You conversation, answer this: Tell me about a time you had to deliver a Threads project with ambiguous requirements

   MediumBehavioralAmbiguity

   How to answer:

   Use STAR: clarify the ambiguity, list options, align stakeholders, deliver an MVP, quantify outcome, and mention what you changed after learning. Emphasize impact, speed, and cross-functional collaboration.

6. Q6

   In a practical product design drill, answer this: Design a low-level audit logger for Threads administrative actions

   MediumLow Level DesignAudit log component

   How to answer:

   Model AuditEvent, Actor, Target, Metadata, Sink, and Redactor; ensure append-only semantics and safe handling of PII. Optimize for simple, scalable product objects and fast iteration.

7. Q7

   In a fast 45-minute Meta-style coding round, solve this: Implement autocomplete over a static set of Marketplace terms

   MediumCodingAutocomplete function

   How to answer:

   Build a trie or sorted array with binary-search prefix range; return ranked top N; test empty prefix, Unicode, and tie ordering. Keep the solution direct and code-ready under time pressure.

8. Q8

   In a Getting-to-Know-You conversation, answer this: Give an example of balancing ship speed and engineering quality for WhatsApp

   MediumBehavioralBalancing speed and quality

   How to answer:

   State deadline and risks, define acceptable quality bar, ship safe slice, add follow-up debt plan, and measure post-launch outcomes. Emphasize impact, speed, and cross-functional collaboration.

9. Q9

   In a fast 45-minute Meta-style coding round, solve this: Implement a batcher for Groups events that flushes by size or time

   HardCodingBatching helper

   How to answer:

   Buffer events, flush when max size or max age is reached, make flush thread-safe, and test empty, timer, size, and failure behavior. Keep the solution direct and code-ready under time pressure.

10. Q10

    In a Meta product/system design round, answer this: Design CDN and origin protection for Marketplace static assets

    HardHigh Level DesignCDN origin shielding

    How to answer:

    Use multi-tier caching, signed URLs, cache keys, origin shield, purge pipeline, health checks, and logs for cache hit-rate analysis. Discuss read-heavy fanout, ranking, privacy, and product trade-offs.

11. Q11

    In a practical product design drill, answer this: Design a configurable cache library for WhatsApp clients

    MediumLow Level DesignCache library

    How to answer:

    Expose Cache<K,V>, EvictionPolicy, ExpiryPolicy, Loader, and Metrics; support LRU/LFU/TTL while keeping thread-safety and testing clear. Optimize for simple, scalable product objects and fast iteration.

12. Q12

    For Meta's content moderation review queues flow, write production-quality backend code to build an LRU cache with TTL and hit/miss metrics while meeting zero-downtime deployment. Describe the main function or class interface, the core data structures, and the edge cases you would test

    MediumCodingCaching

    How to answer:

    A strong answer proposes a small, testable interface and uses hash map plus doubly linked list or ordered dictionary with lazy expiry. It handles retries, invalid input, timeouts, and cleanup explicitly, and states O(1) expected get/put.

13. Q13

    For Meta's WhatsApp message sync flow, write production-quality backend code to implement stale-while-revalidate with request coalescing while meeting limited memory per worker. Describe the main function or class interface, the core data structures, and the edge cases you would test

    MediumCodingCaching

    How to answer:

    A strong answer proposes a small, testable interface and uses serve fresh or bounded-stale values and allow one refresh per key. It handles retries, invalid input, timeouts, and cleanup explicitly, and states O(1) cache lookup with bounded refresh fanout.

14. Q14

    In a Meta backend interview, solve this DSA problem from WhatsApp message sync: implement an LFU cache with LRU tie-breaking. Provide the algorithm, prove correctness, and analyze complexity under peak holiday traffic

    MediumData Structures & AlgorithmsCaching

    How to answer:

    Model the problem with hash maps for keys and frequency buckets with ordered sets. The target solution should achieve O(1) expected get/put, handle empty inputs and ties, and explain why simpler brute-force approaches do not scale.

15. Q15

    In a Meta backend interview, solve this DSA problem from Reels recommendations: identify hot keys from a high-volume request stream. Provide the algorithm, prove correctness, and analyze complexity under 10k requests per second

    HardData Structures & AlgorithmsCaching

    How to answer:

    Model the problem with count-min sketch with heap validation or exact counts for bounded keys. The target solution should achieve sublinear memory for approximate tracking, handle empty inputs and ties, and explain why simpler brute-force approaches do not scale.

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Be fast and correct on coding; for design, drive the conversation; prepare impact-focused behavioral stories

Indicative Backend Engineer pay in India: ~₹10–45 LPA (role-level range, not a Meta-specific figure).

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