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Nash AI

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Nash AI is a technology startup that develops artificial intelligence solutions, typically focused on automating tasks or enhancing productivity through AI-driven tools. As an early-stage company, it operates with a small team building specialized AI products.

5 interview notes · updated Jul 2026

Nash AI·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Had a system design round at Nash AI for a software engineer role. The whole session was basically one big OOP design question about Minesweeper, which sounds toy-ish until you're actually in it trying to articulate class hierarchies and state machines on the spot.
  • Design an object-oriented Minesweeper game. The board is a grid of cells, and each cell has a probability of being a mine. Walk through how per-cell probabilities drive the initial mine layout, define the core classes and their responsibilities, describe how they relate to each other, and specify public APIs for printing the board and handling a user click. Also cover state transitions on a click, how you handle invalid or duplicate clicks, and how your design supports maintainability and testing.

“I started with Cell, Board, Game and felt good about that for about two minutes.”

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Nash AI·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Nash AI system design round focused entirely on a real-time delivery tracking problem. Pretty dense scope for a single session, and I left feeling like I only got through maybe 70% of what they wanted to cover.
  • Design a scalable, fault-tolerant system for real-time delivery tracking where third-party services handle the actual deliveries. Your design should cover the ingestion pipeline, async task queue, idempotency for duplicate updates, retry logic with backoff, storage strategy for current state versus historical events, and how to scale read traffic for status queries.

“This was basically the whole interview in one prompt.”

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Nash AI·Software Engineer·Onsite - Coding / Algorithms

May 2026
Nash AI had me do a live coding round that built directly on a take-home I'd already submitted. Walk them through your own code, then extend it on the spot. It's a smart format but it will expose every shortcut you took the first time around.
  • Walk the interviewer through your take-home solution and explain the design decisions you made.
  • Extend your existing solution to support batch mode, where many inputs are processed in a single invocation instead of one at a time.
  • How does the batch processing path differ from a single-item or streaming path, and what tradeoffs does that introduce?

“I thought this would be the easy part.”

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Nash AI·Software Engineer·Technical Phone Screen

May 2026
Nash AI gave me a coding round that was basically 'build a real game from scratch.' One question, but it had enough moving parts to keep me busy for a while.
  • Implement a Minesweeper game class that takes board dimensions and mine count, randomly places mines on initialization, and supports a click operation that reveals cells, triggers a loss on mines, and recursively reveals connected empty regions. Include a console-based display so the game is actually playable.

“This one took me a minute to even figure out where to start.”

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Nash AI·Software Engineer·Technical Phone Screen

Apr 2026
Technical phone screen at Nash AI for a software engineering role. The main problem was implementing Minesweeper's click logic, which sounds like a toy problem until you're actually in it and they start asking about traversal strategy and complexity.
  • Implement the click(row, col) operation for Minesweeper, covering mine hits, zero-adjacent-mine flood fill, and numbered cell reveals. Also write a function to print the board state.

“I started with the data structures before touching any logic, which turned out to be the right call since they asked about that explicitly anyway.”

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