Reinforce Labs·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

Interviewed for a software engineer role at Reinforce Labs and got a pretty deep backend question about building a REST GET endpoint from scratch. The scope kept expanding as we talked through it, which I wasn't fully prepared for.

Questions Asked (1)

Implement a REST GET endpoint that reads from a data store, handles query parameters like id, filters, and pagination, returns JSON with correct HTTP status codes, and includes input validation and error handling.

API & IntegrationsSystem DesignTechnical Trade-offs

Author's notes

Started fine talking through parsing query params and returning 200 vs 404, but then they asked me to also cover idempotency, caching headers like ETag and Cache-Control, and auth considerations.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then outline the endpoint design covering routing, validation, data access, and response formatting. Walk through the implementation step-by-step, emphasizing error handling and status codes, and conclude with trade-offs and potential improvements.

Pro tip: Demonstrate production readiness by discussing idempotency, rate limiting, and observability (logging, metrics) even if not explicitly asked. Also, mention how you would handle edge cases like invalid pagination parameters or missing resources.

1. Clarify Requirements and Constraints

Ask about the data store (SQL/NoSQL), expected query parameters, authentication, and performance requirements. Confirm the response format and error handling expectations.

2. Design the Endpoint and Routing

Define the URL structure (e.g., GET /resources), specify supported query parameters (id, filters, pagination), and outline how to parse and validate them.

3. Implement Data Access and Business Logic

Describe how to query the data store efficiently, applying filters and pagination. Discuss indexing, query optimization, and handling large result sets.

4. Handle Validation and Errors

Detail input validation (e.g., id format, filter types, pagination limits) and error responses with appropriate HTTP status codes (400, 404, 500).

5. Format Response and Status Codes

Explain how to structure the JSON response (data, metadata for pagination) and choose correct status codes (200 for success, 400 for bad request, 404 for not found, 500 for server errors).

Key Points to Mention

Input validation: validate id format, filter parameters, and pagination limits (e.g., page size max).
Pagination strategies: offset vs. cursor-based, and how to include metadata like total count, next/prev links.
Error handling: consistent error response format, appropriate HTTP status codes, and logging.
Data store query optimization: use indexes, avoid N+1 queries, and consider caching.
Security: prevent injection attacks, sanitize inputs, and enforce authorization.
API design best practices: RESTful naming, versioning, and documentation.

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