Grammarly·Software Engineer·Onsite - System Design / Architecture·Senior

Senior

Jun 2026

Summary

System design round at Grammarly for a software engineer role. The whole thing was one big design question about restaurant reservations, which sounds deceptively simple until you get into the concurrency and scaling parts.

Questions Asked (1)

Design a restaurant reservation system covering requirements, data modeling, booking API, concurrency control, availability search, cancellations, waitlists, notifications, and scaling to high traffic.

System DesignData ModelingAPI & Integrations

Author's notes

This question has a lot of surface area and I think I underestimated it at first.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design the data model and API, and finally dive into concurrency control and scaling strategies. Emphasize how you handle double-booking and high traffic with techniques like optimistic locking and caching.

Pro tip: Proactively discuss trade-offs between consistency and availability, and mention how you would monitor and test the system for race conditions under load.

1. Clarify Requirements and Scale

Ask about expected traffic, peak times, number of restaurants, and whether the system supports multiple locations. Define functional and non-functional requirements.

2. Design Data Model and API

Outline core entities like Restaurant, Table, Reservation, and User. Define RESTful endpoints for searching availability, booking, canceling, and joining waitlists.

3. Address Concurrency and Consistency

Explain how to prevent double-booking using optimistic locking, transactions, or distributed locks. Discuss isolation levels and idempotency for booking requests.

4. Implement Availability Search and Caching

Describe how to efficiently query available slots, possibly using a read-optimized store or cache. Discuss indexing and precomputed availability.

5. Scale and Handle Notifications

Propose scaling strategies like sharding by restaurant, using message queues for notifications, and handling waitlist promotions asynchronously.

Key Points to Mention

Optimistic locking with version numbers to handle concurrent bookings
Idempotent API design to avoid duplicate reservations on retries
Caching availability data with appropriate invalidation strategies
Using a message queue for notifications and waitlist processing
Sharding or partitioning by restaurant ID to scale horizontally
Monitoring and alerting for booking conflicts and system latency

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.