Technical interview guidance

Our technical interviews aren't LeetCode puzzles. In AI Live Coding, you'll build a feature in a real codebase with your own AI tools, and we want to see whether you can direct AI to get something working and catch it when it's wrong. In System Design, you'll design a system out loud, and the focus is your engineering judgment: which constraints you identify, which tradeoffs you make, and how you defend them. This guide covers what to expect in each session, what we evaluate, and how to prepare. You don't need experience with our tech stack or in healthcare.

Session	Length
AI Live Coding	60 minutes
System Design	60 minutes

1. AI Live Coding

60 minutes · AI tools required · Your own laptop

You'll get access to an existing codebase built specifically for this interview and be asked to implement a feature in it. It works like a real development environment. The exercise assesses how you build software with AI, not whether you can finish an artificially large task in 60 minutes.

Required: You are required to use an AI coding assistant during this session. Please use your own laptop and come prepared with your preferred AI tools and development environment. By the end of the session, get the core feature working and show it running or tests passing.

No personal AI subscription? If you don't have a personal coding agent subscription like Claude or Codex, we'll reimburse a standard-tier 1-month subscription. Send your receipt to your recruiter.

Pro tip: Use responsive AI settings, not slow deep-reasoning modes. Skip workflow overhead that doesn't directly move the implementation forward, like writing a custom skill or building an elaborate architecture map.

Work however you normally do: a traditional IDE, a terminal-first workflow, AI agents, or a mix. You aren't expected to write the code by hand during this assignment. Use AI to explore the codebase, generate implementations, iterate, and debug, and start early. We're interested in how you direct the work, evaluate the output, make decisions, and validate results.

Don't avoid AI to prove you can code without it. That isn't the signal we're looking for. Treat AI output as a starting point. When it gives you 50 lines of code, read them, catch what's wrong, and tell us what you're keeping and what you're changing. A candidate who ships working code with AI while narrating their thinking will do better than one who writes everything from scratch. A candidate who pastes AI output without reviewing it will do worse than either.

You are not expected to complete every possible enhancement, but you need to get the core feature working. Real progress, sound judgment, and a clear understanding of what remains before it could ship can meet the bar.

How to pace your interview

• Orient quickly. A good pattern is to have your agent map the codebase and propose a plan, then check that plan yourself before any code gets written. If a requirement is ambiguous, ask.
• Keep planning short and start implementing early.
• Protect time at the end to run the feature, review the code, and write tests beyond the happy path.

What we're evaluating

• Codebase orientation: How quickly and effectively you understand an unfamiliar codebase and identify the areas relevant to the task. We want to see you break the work into clear deliverable tasks and identify important tradeoffs during planning.
• Problem solving and orchestration: How you break down the feature request, plan the implementation, and coordinate work between yourself and your AI tools. We want to see AI used as a primary tool for both exploration and implementation, with well-scoped prompts and critical review of output.
• Communication: How clearly you explain your thinking and decision-making throughout the session. Think out loud as you work. Narrate what you're reading, what you're deciding, where you're unsure, and what the AI gave you. If you're stuck, say so. If you don't tell us why you accepted, rejected, or changed what the AI gave you, we can't give you credit for it.
• Engineering judgment: Do you read what the AI generates? Do you catch problems and make independent engineering decisions? Catch issues beyond syntax, such as wrong patterns and missing edge cases, and write tests that go beyond the happy path. Before you wrap up, tell us what's still risky or unfinished.

For Staff engineers: Staff engineers are expected to operate at a system level throughout this session. That means seeing the feature in its architectural context, treating AI as core infrastructure with a deliberate workflow, and reviewing generated code for maintainability and extensibility, not just correctness.

Pre-interview setup checklist

Please complete the following before your interview:

• Install your preferred language runtime: Go 1.23+, Python 3.12+, Node.js 20+ (for TypeScript), or Java 21+
• Make sure Git is installed and configured
• Install Docker (v27+) and Docker Compose (v2.31+)
• Have your preferred editor and AI tooling ready
• Send your recruiter your GitHub username and preferred programming language, so we can grant you repository access before the session

Your recruiter will confirm the exact versions when your interview is scheduled.

Commonly used AI development tools

If you'd like to explore or refine your tooling before the interview, these are commonly used options. Use what reflects how you normally build software. Familiarity matters more than novelty.

Category	Examples
AI-first editors	Cursor, Windsurf, Zed
In-editor and terminal-based assistants	Claude Code, GitHub Copilot, Continue

2. System Design

60 minutes · Virtual · Whiteboard required

Your interviewer will share an Excalidraw link at the start of the session, and you'll use it as your whiteboard throughout. If you haven't used Excalidraw before, spend a few minutes with it beforehand.

You'll work through a high-level business problem with your interviewer.

You may also discuss concepts such as caching, synchronous and asynchronous workflows, API design, and data modeling. Explicit requirements such as auditability, latency, and scale are required parts of the discussion. Additional concerns you raise on your own can distinguish a stronger design, but they aren't hidden pass/fail requirements. Time is reserved at the end to discuss risks, validation, monitoring, and what you'd change before production.

The session is collaborative. Expect to answer questions, receive feedback, and refine your approach as you go. There's no single correct answer. The interviewer is interested in how you think, how you identify the system's key constraints, and how you make and defend architectural choices among competing priorities.

Own your interview: We'll give you the problem and a few baseline constraints, then hand the session over to you. At some point, we'll introduce a new requirement for you to incorporate into your existing design. We want to see how you adapt rather than start over.

What we're evaluating

• System architecture: How you structure service boundaries and data flows to support a reliable, production-ready system. We're interested in how you think about the separation between components, not just which components you choose.
• Handling complexity: How you approach reliability, performance, and scaling in high-traffic environments. Think about what happens at scale and under load, not just in the happy path. Find the core tensions in the system on your own.
• Design tradeoffs: When you make a design choice, tell us what you're optimizing for and what you're giving up. Naming a tension isn't enough; we want to hear you resolve it and defend your reasoning.
• Communication: Ask clarifying questions before you start. Good questions signal that you understand what matters in a system. Treat us as collaborators throughout, not an audience, and narrate your assumptions as you go.

For Staff engineers: Staff engineers are expected to drive this session at a higher altitude: proactively surfacing constraints beyond the obvious, connecting tradeoffs to downstream consequences, and leading the conversation rather than responding to it.

A few practical tips

• Clarify first. Pin down any constraints that would meaningfully change your design before you touch the whiteboard.
• Work top-down. Establish the major components and data flows before diving into any single piece.
• Don't neglect operations. How you'd detect problems, handle failures gracefully, and recover from degraded states is as important to us as the core architecture itself.
• Prioritize. You won't cover everything in an hour, so spend your time on the most important risks and say what you're setting aside.

Our cultural values

At Hinge Health, culture is part of how the work gets done. Five values we live by:

Value	What it means
Effective Communication	Say it clearly, say it early, say the thing that moves the work forward.
Lead at All Levels	You don't need the title to see the gap and take the step.
Hustle	Bias for action means momentum with judgment.
Accountability	Own the outcome and learn from it.
Learn It All	Curiosity is how we scale. Learn fast and adjust faster.

If you move on to the onsite, read our onsite interview guidance. Questions about your interview? Reach out to your recruiter. We're rooting for you.