---
title: Acing AI-Allowed Technical Interviews for Senior/Staff Engineers in Fast-Growing Healthtech Startups
created: 2026-03-19
updated: 2026-03-19
type: summary
tags: ["AI", "engineering", "interview", "notes", "telegram"]
external: http://go/ui/posts/2212/
status: inbox
---

This is an excellent position to be in. Heidi Health is a fast-growing, AI-native healthtech startup, and the fact that they encourage AI tools in the interview completely flips the traditional script. 

When an interviewer lets you use AI, they are no longer testing your ability to memorize syntax or standard library functions. They are testing you as an architect, an editor, and an operator. Here is exactly what matters in this format and how you can prepare to ace it as a Senior/Staff engineer.

### What Actually Matters in an AI-Allowed Interview

If the AI is acting as your junior developer, the interviewer is evaluating how you manage it:

* **Problem Decomposition:** The AI can write the functions, but *you* have to define what functions need to be written. Can you break a complex problem into logical, testable chunks?
* **Prompt Engineering & Tool Fluency:** How fast and effectively can you guide the AI? They want to see if you can write clear, bounded prompts rather than fighting with the tool when it hallucinates.
* **Verification and Skepticism:** AI writes plausible but sometimes subtly flawed code. Your ability to spot edge cases, security flaws, off-by-one errors, and inefficient time/space complexities is critical. Blindly copy-pasting is an instant red flag.
* **Test-Driven Thinking:** Because the code is generated instantly, the focus shifts to validation. Writing strong test cases *before* or alongside the code demonstrates maturity.

### How to Prepare Your Environment

Do not waste a single minute of a 60-minute call on setup.

* **Choose Your Weapon:** Decide if you are using GitHub Copilot, Cursor, or a browser window with ChatGPT/Claude. Cursor is highly recommended for this flow as it integrates seamlessly.
* **Prepare Your Workspace:** Have your IDE open, a blank project initialized, a testing framework ready (e.g., `pytest` if you use Python, or `go test` for Go), and your screen-sharing settings configured.
* **Practice "Prompt-Driven Development":** Do a few practice runs where you solve algorithm questions by writing extensive, structured comments first, and letting the AI fill in the code based on your comments. 

### Senior/Staff Engineer Tips for the Interview

As an engineer with over a decade of experience, you need to elevate the conversation beyond just solving the algorithm. 

* **Focus on the "Ilities":** While the AI writes the logic, you should be talking out loud about scalability, maintainability, and observability. Ask clarifying questions like, *"What is the expected load for this?"* or *"How would this handle a network timeout if we were fetching this data from an external API?"*
* **Think Like a Platform Engineer:** Bring your infrastructure mindset to the code. If you are asked to parse logs, structure data, or build a small rate limiter, discuss how this code would behave in a containerized environment, how you would monitor it (Datadog/Prometheus), or how you would handle deployment rollbacks. 
* **Drive the Session:** Treat Sufiyan (the interviewer) as a collaborative peer. Narrate your thought process constantly: *"I'm going to ask the AI to generate a trie structure for this, but I'm keeping an eye on memory consumption because..."*

### Decoding the "STAR Format" Request

It is unusual for a company to ask for the STAR format (Situation, Task, Action, Result) in a purely coding-focused round. This means they are likely doing a hybrid interview: you will code, but they expect you to draw parallels to your past work.

* **Link Code to Experience:** While solving the problem, you might say, *"I'm structuring the error handling this way because in a past role, we had a severe incident where swallowed exceptions caused a silent failure in our CI/CD pipeline. The result was a massive backlog, so now I enforce strict early-exit error handling."*
* **Have 3-4 Stories Ready:** Prepare a few concise stories about major architectural challenges you've solved, automation you've built, or scaling bottlenecks you've overcome. Be ready to deploy these stories if the interviewer pauses the coding to ask behavioral questions.

Would you like to do a quick mock run right now, where I give you a typical Senior DevOps coding scenario and we practice how you would prompt an AI and narrate your thought process?
