Hippocratic AI·Software Engineer·Take-home Assignment·Intermediate

Intermediate

May 2026

Summary

Take-home assignment for a software engineering role at Hippocratic AI. The task was building an AI agent staffing scheduler from a CSV input, outputting hour-by-hour coverage needs for a full Pacific-time day. Pretty open-ended with a CLI requirement and an optional UI stretch goal.

Questions Asked (1)

Given a CSV of patient call requirements, build a scheduler that computes hour-by-hour AI agent staffing needs, broken down both in total and per customer, for a single Pacific-time day. A CLI demo is required; a UI is a bonus.

System DesignTechnical Trade-offsAdaptability & Ambiguity

Author's notes

The open-endedness was the hardest part.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and assumptions, then outline a modular system design that separates data ingestion, scheduling logic, and output presentation. Emphasize handling time zones, concurrency, and scalability, and discuss trade-offs between simplicity and extensibility. Conclude with a CLI demo plan and optional UI considerations.

Pro tip: Demonstrate awareness of real-world complexities like daylight saving time and varying call durations, and propose a configurable, testable architecture. This shows maturity beyond a naive implementation.

1. Clarify Requirements and Assumptions

Ask questions to understand the CSV schema, call requirements, and constraints (e.g., call durations, agent availability, time zone handling). State assumptions explicitly to avoid ambiguity.

2. Design Data Model and Ingestion

Define how to parse the CSV, validate data, and represent call requirements (e.g., per customer, per hour). Consider using a database or in-memory structures for flexibility.

3. Develop Scheduling Algorithm

Outline an algorithm to compute hour-by-hour staffing needs, aggregating total and per-customer requirements. Discuss handling of overlapping calls, peak times, and time zone conversion to Pacific.

4. Implement CLI and Optional UI

Describe a CLI interface that takes CSV input and outputs staffing needs (e.g., table or JSON). Mention a simple UI (e.g., web dashboard) as a bonus, focusing on core functionality first.

5. Discuss Trade-offs and Scalability

Address trade-offs between accuracy and performance, and how the design scales with more customers or finer time granularity. Mention testing and error handling.

Key Points to Mention

Time zone handling: converting all times to Pacific and accounting for daylight saving time.
Data validation and error handling for malformed CSV rows.
Algorithm complexity and optimization for large datasets (e.g., using interval trees or bucketing by hour).
Modular design: separating concerns for maintainability and testability.
CLI usability: clear output format, arguments for input file and time zone.
Optional UI: simple web interface using a framework like Flask or React, but prioritize CLI.

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