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Ramp·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jul 2026

Summary

Ramp software engineer interview that focused on building a recipe manager service from scratch. Pretty design-heavy for a coding round, less about raw algorithm chops and more about how you think through data organization and API contracts.

Questions Asked (1)

Q1

Design and implement a recipe manager service with full CRUD support, where each recipe gets an auto-incremented string ID like 'recipe1', 'recipe2', and recipe names must be unique in a case-insensitive way.

System DesignData ModelingAlgorithms & Data Structures
Author's notes

The ID generation part was straightforward, just a counter.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design a data model with a hash map for case-insensitive name uniqueness and a counter for auto-incremented IDs. Implement CRUD operations with proper error handling, and discuss trade-offs like concurrency and persistence.

Pro tip: Mention that you would use a case-insensitive map (e.g., lowercased name as key) to enforce uniqueness efficiently, and consider thread-safety if the service is concurrent. Also, discuss how you would handle ID generation in a distributed system.

1. Clarify Requirements

Ask about expected scale, concurrency, persistence needs, and whether IDs should be globally unique or per-user. Confirm CRUD operations and uniqueness constraints.

2. Design Data Model

Propose a Recipe class with fields (id, name, ingredients, steps, etc.). Use a hash map to store recipes by ID and another map (or set) to track lowercased names for uniqueness. Maintain a counter for ID generation.

3. Implement CRUD Operations

For create: check name uniqueness, generate ID, store recipe. For read: fetch by ID. For update: validate new name uniqueness, update fields. For delete: remove from both maps.

4. Handle Edge Cases and Concurrency

Discuss thread-safety (e.g., synchronized methods or concurrent maps), error handling for duplicate names or missing IDs, and potential race conditions in ID generation.

5. Discuss Scalability and Extensions

Mention how to scale (e.g., database with unique index on lowercased name, distributed ID generator) and possible extensions like search, pagination, or versioning.

Key Points to Mention

  • Case-insensitive uniqueness: store lowercased names in a set or map to check duplicates efficiently.
  • Auto-incremented string ID: use a counter and format as 'recipe' + counter, ensuring thread-safe increment.
  • Data structures: hash map for O(1) lookup by ID, and another map for name-to-ID mapping.
  • Concurrency: use synchronized blocks, ConcurrentHashMap, or atomic integers to handle concurrent requests.
  • Persistence: consider using a database with a unique index on lowercased name and an auto-increment column for ID.
  • Error handling: return appropriate errors (e.g., 409 Conflict for duplicate name, 404 Not Found for missing recipe).

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