OpenAI Interview Questions — Page 62

OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

OpenAI SWE interview with a pretty gnarly scheduling problem that had a deceptively tricky follow-up. The core question was manageable but the prefix-balancing constraint in the follow-up is where things got real.

You're given a data labeling platform with totalTask, totalModel, totalHuman, and k as inputs. Return a list of [task, model, human] assignment tuples such that every human appears in at least k assignments, no human annotates the same task twice, and all IDs are valid. Return an empty list if no valid schedule exists.
Follow-up: modify the schedule so it's prefix-balanced. For every prefix of the output list, the number of times each model has been assigned to a task and the number of times each model has been paired with a human must each differ by at most 1 across all models (including models with zero assignments so far).

“Spent the first few minutes just making sure I understood the constraints correctly, because the 'same human can't annotate the same task twice' part interacts weirdly with the k-minimum requirement when totalHuman is large relative to totalTask.”

View Post

OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

A 75-minute coding interview at OpenAI for a SWE role where the task was to design a custom data structure optimized for both reads and writes. No ML, no fancy algorithms, just engineering judgment and clean code. Felt more like a design conversation than a grind session.

Design and implement a custom data structure that is optimized for both read and write operations. Define a reasonable API, explain the trade-offs, and walk through working code with examples.

“The open-endedness is what gets you.”

View Post

OpenAI·Software Engineer·Onsite - System Design / Architecture

Jul 2026

System design round at OpenAI for a software engineer role, focused entirely on building a browser-based cloud IDE with sandboxed code execution. Deep dive, lots of follow-ups, felt more like a working session than a standard interview.

Design a sandboxed, browser-based cloud IDE similar to Google Colab or Replit. Users can open notebooks in the browser, code runs on a backend container, and output streams back in real time with persistent storage and multi-user isolation.
How would you manage a pool of execution containers, handling cold starts, warm pool sizing, autoscaling, and idle eviction?
What sandboxing approach would you use to safely isolate untrusted user code running on your backend?
How would you stream stdout and stderr from a running container back to the user's browser in real time?
How would you handle file persistence and storage quotas for users across sessions?
How would you garbage collect idle sessions cost-effectively without disrupting active users?

“This is a beast of a question.”

View Post

OpenAI·Software Engineer·Onsite - System Design / Architecture

Jul 2026

System design round at OpenAI for a SWE role, focused on payment systems. The scope kept shifting between generic payment infrastructure and specific verticals like coffee-shop POS, which tripped people up badly if they came in with a memorized template.

Design a payment system for a coffee-shop ordering flow, including the hold and charge lifecycle and nightly batch settlement.
How do you handle idempotency across the hold, charge, and batch settlement steps to prevent double-charging or double-settling?
Walk me through the exact table schema for transactions, including which fields are primary/partition keys, sort keys, and what indexes you'd add for the nightly batch query.
What happens when the payment processor is unreachable mid-transaction? Walk through your resilience strategy.
How would you scale this system to 10x traffic, and what changes if you need to launch globally?
For a tap-to-pay card processor with a strict low-latency requirement, which parts of the flow should stay synchronous and which can be deferred to an async queue?

“The title of the prompt said 'Payment' so I went straight into generic payment infrastructure mode.”

View Post

OpenAI·Software Engineer·Onsite - System Design / Architecture

Jul 2026

OpenAI system design round focused entirely on building a distributed rate-limiting service from scratch. The scope was way broader than I expected, covering everything from algorithm selection to multi-region consistency to how you'd evolve the architecture over time.

Design a distributed rate-limiting service with an API like allow(key, cost). Walk through your algorithm choices, enforcement model, and how you'd back it with Redis.
How would you handle clock skew across nodes in a distributed rate limiter, and what are the implications for your chosen algorithm?
Should the rate limiter fail open or fail closed if the backing store becomes unavailable? Justify your choice.
How would you evolve the architecture from per-host rate limiting to a centralized service, and then further to a hierarchical model spanning host, region, and global limits?
How do you ensure fairness across tenants in a shared rate-limiting infrastructure, especially when traffic patterns are uneven?

“This was the core question and it ate the whole session.”

View Post

OpenAI·Software Engineer·Onsite - Coding / Algorithms

Jul 2026

OpenAI SWE coding round focused on numerical computing, specifically computing entropy from logits in a way that doesn't blow up for large values. Two parts: a batch implementation and a streaming version with O(1) space. Pretty niche but actually a fair test of whether you understand floating point.

Implement a numerically stable function that computes entropy from a list of logits (unnormalized log-probabilities), without naively computing softmax probabilities first. Must handle logit values up to plus or minus 10,000.
Design a StreamingEntropy class that processes logits one at a time with O(1) memory and computes the same numerically stable entropy at the end. The tricky part: the running maximum can change as new logits arrive.

“The naive approach of exponentiating the logits directly just produces inf or 0 for large inputs and you get garbage.”

View Post

OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

A probability and simulation question for a software engineering role at OpenAI. The whole thing was math-heavy in a way I didn't fully expect from a coding screen. Not terrible, but it required you to actually remember your stats.

A point source at the origin emits particles toward a vertical screen at x = 1. Each particle travels at an angle theta sampled uniformly from [-pi/2, pi/2]. What is Y, the y-coordinate where the particle hits the screen, as a function of theta?
Derive the CDF and PDF of Y given that theta is uniform on [-pi/2, pi/2].
Write a simulation that generates many particles using this setup and verifies the theoretical distribution by comparing a histogram of hit locations to the true PDF.
What numerical or visualization problems would you anticipate when running this simulation?

“This part was straightforward.”

View Post

OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

OpenAI full-stack interview that was essentially one long live-coding session: build a ChatGPT-style chat UI in React from scratch. The scope was bigger than I expected and the edge case discussion at the end caught me a bit flat-footed.

Build a ChatGPT-style web chat interface in React. It needs a message list showing user and assistant turns with proper styling and auto-scroll, an input bar with send button, Enter-to-send, shift+Enter for newlines, and a disabled state while a response is pending, plus a loading/typing indicator.
How would you implement streaming responses, where tokens arrive incrementally and get appended to the latest assistant message in real time?
Walk through how you'd handle cancellation if the user wants to abort a streaming response mid-flight.
How would you structure the component decomposition for this chat UI?
What edge cases would you consider for this chat interface, such as error handling, empty input submissions, and very long messages?

“The core UI part went okay.”

View Post

OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

Interviewed for a software engineering role at OpenAI and got hit with a grid simulation problem that looked like a BFS variant but had enough wrinkles to slow me down. The death-marking mechanic was the part that tripped me up at first.

You're given an m x n grid where each cell is in one of four states: uninfected, infected, immune, or dead. Two thresholds control the spread. An uninfected cell gets infected if at least infectThreshold of its 8 neighbors are currently infected. When a cell gets infected, if at least deathThreshold of those same neighbors are infected, the cell is marked to die instead of recovering. Infected cells last exactly one day then resolve. Simulate this until the grid stops changing and return the final state.

“The simultaneous update rule is what gets you if you're not careful.”

View Post

OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

OpenAI iOS Engineer interview that was more software architecture than anything mobile-specific. The whole session revolved around refactoring a chatbot codebase, which I wasn't expecting going in.

You're given a monolithic chatbot codebase. How would you break it apart into well-defined modules, and where do you draw the boundaries between them?
How would you introduce dependency injection into this codebase so that each component can be tested in isolation?
There are hardcoded values scattered throughout the codebase. What's your approach to replacing them with configuration, and how do you decide what actually belongs in config versus code?
Walk me through how you'd add tests to a codebase that wasn't designed with testability in mind.

“I went with the obvious split: intent parsing, dialog management, response generation, persistence.”

View Post