OpenAI Software Engineer interview

Tests: API design and careful state management across calls - exactly the kind of component work OpenAI's loop favors.

Approach: Decide what minimal state uniquely identifies a position (index, or a stack for nested structures) and make save/restore round-trip through that state. Later parts typically nest iterators or add serialization, so keep state explicit rather than relying on closures.

Tests: Choosing data structures for temporal lookups and extending a simple store cleanly as constraints grow.

Approach: Store per-key lists of (version, value) pairs appended in order, then binary-search for the latest version at or before the query. Think ahead to follow-ups like deletes or range reads before locking in your layout.

Tests: Structuring a small system so each new requirement slots in without rewrites - and writing a lot of correct code fast.

Approach: Separate storage from query logic from the start: rows in simple structures, filtering and aggregation as composable functions. The staged format punishes shortcuts taken in part one.

Tests: Careful edge-case handling ('..', '.', absolute vs relative) plus cycle-safety once symlinks enter.

Approach: Normalize with a stack of path segments first. The symlink extension is the real test: substitute link targets during traversal and guard against cycles with a visited set or hop limit.

Tests: Extending correct sequential traversal into safe concurrent execution.

Approach: BFS with a frontier queue and a visited set, then parallelize fetches with a thread pool or asyncio. The interviewer is watching how you keep the visited set race-free and how you bound concurrency.

Tests: Modeling dependencies and recomputation - a compact version of real incremental-computation systems.

Approach: Treat cells as nodes in a dependency graph and evaluate in topological order, detecting cycles. Follow-ups usually add updates, so think about invalidating and recomputing only affected cells.

Tests: Precision with byte- and string-level formats and handling values that contain your delimiter.

Approach: Length-prefixing sidesteps delimiter collisions: write each field as length then bytes. Get the parse loop airtight - off-by-one reads are where candidates lose this one.

Tests: How you navigate unfamiliar code - the daily job - rather than how you start from a blank page.

Approach: Read the tests and entry points first, narrate your model of the code, and reproduce the bug before touching anything. One candidate found the goals unclear, so ask directly what done looks like.

Tests: Adapting classic scaling patterns to AI serving: GPU capacity, streaming responses, and graceful degradation.

Approach: Start with the request path (gateway, queueing, model workers), then attack the AI-specific parts: request batching, token streaming, rate limiting, and what fails first under load. Name the bottleneck before proposing fixes.

Tests: Reliability engineering: at-least-once delivery, retries, and protecting your system from slow consumers.

Approach: Durable queue per destination, retries with exponential backoff and jitter, idempotency keys, and dead-letter handling. Discuss ordering guarantees explicitly - interviewers probe whether you know what you are promising.

Tests: Designing around expensive, slow, GPU-bound work rather than fast request-response.

Approach: Model it as a job system: submission, queueing with priorities, worker pools on GPU capacity, progress reporting, and artifact storage plus CDN delivery. Cost and capacity math earns points here.

Tests: Whether your interest is specific and considered, not generic AI enthusiasm.

Approach: Ground your answer in something concrete - a product decision, a research direction, or a deployment tradeoff you have a real opinion on. Candidates report that vague excitement is screened out as early as the recruiter call.

Tests: Depth of ownership - whether you can defend the architecture, alternatives, and outcomes of work you claim.

Approach: Choose your most complex project, not your most polished story. Interviewers drill down layer by layer, and experienced candidates call this the toughest round - rehearse the why behind every major decision.

Tests: The official guide's stated priorities: collaboration, communication, and openness to feedback.

Approach: Expect these sprinkled inside technical interviews rather than in one dedicated slot. Keep two or three short, true stories ready about disagreement, feedback you acted on, and unblocking another team.