OpenAI
Leading AI research laboratory developing state-of-the-art foundation models like GPT-4.
5 Rounds
~21 Days
Very Hard
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Backend Engineer
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Behavioral
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medium
Tell me about a time you had to make a technical tradeoff between shipping quickly and building a perfectly scalable system.
#Trade-offs
#Productivity
#Decision Making
Backend Engineer
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Behavioral
•
medium
Describe a situation where you had to debug a complex production incident under high pressure. What was your process?
#Incident Response
#Debugging
#Communication
Backend Engineer
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Behavioral
•
medium
How do you handle working on a project where the requirements are highly ambiguous and constantly changing?
#Ambiguity
#Adaptability
#Agile
Backend Engineer
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Behavioral
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medium
Tell me about a time you disagreed with a senior engineer or manager about a system architecture. How did you resolve it?
#Conflict Resolution
#Communication
#Influence
Backend Engineer
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Behavioral
•
medium
Describe a time you identified a major bottleneck in a system and took the initiative to fix it without being asked.
#Initiative
#Performance Optimization
#Ownership
Backend Engineer
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Behavioral
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medium
OpenAI moves at a very fast pace. Tell me about a time you had to learn a completely new technology to deliver a project on tight deadlines.
#Learning Agility
#Time Management
#Adaptability
Backend Engineer
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Behavioral
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hard
What is the most complex distributed systems failure you have ever encountered, and what did you learn from it?
#Post-mortems
#Distributed Systems
#Resilience
Backend Engineer
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Coding
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easy
Given an array of API request start and end times, calculate the maximum number of concurrent requests the server handled.
#Arrays
#Sorting
#Sweep Line
Backend Engineer
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Coding
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medium
Implement a token bucket rate limiter that can handle both requests-per-minute and tokens-per-minute limits simultaneously.
#Concurrency
#Data Structures
#Rate Limiting
Backend Engineer
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Coding
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medium
Write a function to merge K sorted streams of tokens into a single sorted stream. Assume the streams are coming from different backend model replicas.
#Heaps
#Streaming Data
#Pointers
Backend Engineer
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Coding
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medium
Implement a thread-safe LRU Cache with a Time-To-Live (TTL) for each entry. This would be used to cache recent prompt embeddings.
#Hash Maps
#Linked Lists
#Concurrency
Backend Engineer
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Coding
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hard
Given a stream of nested JSON chunks (which may be fragmented), write a parser that yields valid JSON objects as soon as they are fully formed.
#String Manipulation
#Parsing
#Stacks
Backend Engineer
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Coding
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medium
Implement a Trie data structure optimized for fast prefix matching to detect blocked keywords in a streaming prompt.
#Trees
#Trie
#String Matching
Backend Engineer
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Coding
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hard
Serialize and deserialize an N-ary tree. This is used to represent branched conversation threads where users edit previous prompts.
#Trees
#Serialization
#DFS/BFS
Backend Engineer
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Coding
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hard
Implement a text justification algorithm. Given an array of words and a maximum width, format the text such that each line has exactly the maximum width.
#String Manipulation
#Greedy Algorithms
Backend Engineer
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Coding
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medium
Find the longest substring with at most K distinct characters. (Used to optimize context window parsing).
#Sliding Window
#Hash Maps
#Strings
Backend Engineer
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Coding
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hard
Implement a distributed task queue executor. You have a central queue and multiple worker nodes. Ensure tasks are executed exactly once.
#Distributed Systems
#Concurrency
#State Machines
Backend Engineer
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Coding
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medium
Write a program to resolve dependencies for a set of AI agents. Given a list of agents and their dependencies, output a valid execution order.
#Graphs
#Topological Sort
#BFS/DFS
Backend Engineer
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System Design
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hard
Design the OpenAI API rate limiting system. It needs to enforce limits on requests per minute (RPM) and tokens per minute (TPM) across millions of users globally with minimal latency.
#Distributed Systems
#Redis
#Latency Optimization
Backend Engineer
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System Design
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hard
Design a system for streaming LLM responses to millions of concurrent users. How do you handle connection drops and ensure tokens are delivered in order?
#Server-Sent Events (SSE)
#WebSockets
#Load Balancing
#Connection Management
Backend Engineer
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System Design
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hard
Design a webhook delivery system for asynchronous API requests (e.g., batch processing of millions of prompts).
#Message Queues
#Retry Mechanisms
#Idempotency
#Rate Limiting
Backend Engineer
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System Design
•
hard
Design a GPU resource scheduler for batch processing inference jobs. Some jobs have higher priority, and GPUs have varying memory capacities.
#Resource Allocation
#Scheduling Algorithms
#Distributed Systems
Backend Engineer
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System Design
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medium
Design ChatGPT's conversation history storage system. It must support fast retrieval of recent chats, full-text search, and handle massive write volume.
#Databases
#Sharding
#Search Engines
Backend Engineer
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System Design
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hard
Design a system to detect and block malicious prompts (jailbreaks) in real-time before they reach the LLM.
#Security
#Stream Processing
#Machine Learning Infrastructure
Backend Engineer
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System Design
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medium
Design a scalable distributed cache for LLM prompt/response pairs to save compute on identical queries.
#Caching
#Hashing
#Consistency
Backend Engineer
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System Design
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hard
Design an ingestion pipeline for training data that continuously processes petabytes of text from the web.
#Data Engineering
#Kafka
#MapReduce
#Storage
Backend Engineer
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System Design
•
medium
Design a real-time monitoring and alerting system for model inference latency across multiple geographic regions.
#Observability
#Time-Series Databases
#Data Aggregation
Backend Engineer
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System Design
•
hard
Design a vector database for storing and querying billions of embeddings generated by our models.
#Vector Search
#ANN Algorithms
#Sharding
#Databases
Backend Engineer
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Technical
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medium
How would you optimize a Python backend service that is CPU-bound due to heavy JSON serialization/deserialization?
#Python
#Profiling
#Serialization
Backend Engineer
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Technical
•
medium
Explain how Server-Sent Events (SSE) work under the hood. What are the load balancing challenges associated with SSE?
#HTTP
#Load Balancing
#TCP/IP
Backend Engineer
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Technical
•
hard
How do you manage memory leaks in a long-running Python asyncio application?
#Memory Management
#Asyncio
#Garbage Collection
Backend Engineer
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Technical
•
easy
What are the trade-offs between gRPC and REST for internal service-to-service communication in a high-throughput environment?
#gRPC
#REST
#Microservices
Backend Engineer
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Technical
•
hard
Explain the Raft consensus algorithm. How does it handle network partitions?
#Consensus
#Raft
#Fault Tolerance
Backend Engineer
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Technical
•
medium
How do you handle database migrations in a high-availability system with zero downtime?
#Database Migrations
#High Availability
#Deployment
Backend Engineer
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Technical
•
medium
Describe how you would implement distributed tracing across microservices handling LLM requests to identify latency spikes.
#Distributed Tracing
#Microservices
#OpenTelemetry
Difficulty Radar
Based on recent AI-sourced data.
Meet Your Interviewers
The "Standard" Interviewer
Senior EngineerFocuses on core competencies, system constraints, and clear communication.
SimulateUnwritten Rules
Think Out Loud
Always explain your thought process before writing code or drawing architecture.