The 90-Minute Technical Vetting Playbook for SaaS Teams (2026)
Quick Answer: Interview Structure by Role Level
| Role level | Interview approach | Duration |
|---|---|---|
| Junior (0–2 years) | Practical coding task + culture/communication | 60 minutes |
| Mid-level (3–5 years) | Practical task + basic system design | 75 minutes |
| Senior (5–8 years) | Deep dive + practical task + system design | 90 minutes |
| Tech lead / Staff | Architecture discussion + leadership scenarios | 90–120 minutes |
| First engineer hire | All of above + "build something small" async | 90 min + async |
Skip LeetCode. Abstract algorithmic puzzles select for interview-practice, not SaaS engineering quality. Use practical tasks that mirror the actual job: debug a React hook, design a database schema for a feature you described.
Who Is This Guide For?
| If you are... | Focus on |
|---|---|
| Founder hiring first engineer | Full 90-min playbook + red flags section |
| Engineering manager, building a team | Phase 1 (deep dive) + scoring rubrics |
| Recruiter screening technical candidates | Phase 4 (soft/culture) + red flags |
| CTO creating a hiring process | Full playbook + scoring rubric |
Hiring the wrong engineer costs a SaaS company roughly $50,000 to $100,000 in lost time, recruiting fees, and technical debt. Yet, most companies still rely on unstructured chats or irrelevant whiteboard puzzles.
At Moydus, we use a rigorous 90-minute protocol to vet top 1% talent. This isn't about trick questions; it's about simulating the actual job.
The 90-Minute Agenda
| Time | Phase | Focus |
|---|---|---|
| 00:00 - 00:20 | Phase 1: Deep Dive | Verifying depth of past experience |
| 00:20 - 01:00 | Phase 2: Practical Task | Real-world problem solving (Live) |
| 01:00 - 01:20 | Phase 3: System Design | Architecture & Scalability thinking |
| 01:20 - 01:30 | Phase 4: Culture/Soft | Communication & Team fit |
Phase 1: The "Deep Dive" (20 Minutes)
Goal: Detect 'Passenger' vs. 'Driver' behavior.
Don't ask: "Tell me about your background." Ask: "Pick the most complex system you built in the last 2 years. Draw the architecture. What was the single hardest technical constraint you faced, and how specifically did you solve it?"
What to look for:
- Drivers explain trade-offs (e.g., "We chose Postgres over Mongo because we needed ACID compliance for transactions...").
- Passengers explain events (e.g., "We used React because that's what the team was using.").
Phase 2: The Practical Task (40 Minutes)
Goal: Assess coding fluency and debugging skills.
Rule #1: No LeetCode. Reversing a binary tree on a whiteboard proves nothing about building a SaaS product.
The Task: Provide a realistic, slightly broken code snippet (e.g., a React component with a useEffect infinite loop or a Node.js API endpoint with a race condition).
The Prompt: "Here is a piece of code that is failing in production under high load. Talk me through how you would debug this, and let's refactor it together."
Scoring Criteria:
- Tooling: Do they use the debugger/console effectively?
- Communication: Do they explain their thought process out loud?
- Safety: Do they consider edge cases (null checks, error handling)?
- Modern Syntax: Are they using 2026 standards (e.g., TS 5.x features)?
Phase 3: System Design (20 Minutes)
Goal: Test ability to scale and architect.
The Prompt: "Design a simplified version of Slack's real-time messaging system."
Key Checkpoints:
- Database: Do they suggest a suitable DB (e.g., Cassandra/DynamoDB for messages)?
- Real-time: Do they mention WebSockets?
- Scale: How do they handle 1 million concurrent users? (Load balancers, sharding, caching strategies).
- Trade-offs: Do they acknowledge the cost/complexity of their choices?
Phase 4: Cultural & Communication Fit (10 Minutes)
Goal: Ensure they raise the bar for the team.
The "No Jerks" Rule: Even a 10x engineer will destroy a startup if they are toxic.
Key Questions:
- "Tell me about a time you disagreed with a Product Manager or Designer. How did you resolve it?"
- "How do you handle code reviews? Give me an example of feedback you gave recently."
The Scoring Matrix
We score every candidate on a 1-5 scale across 4 dimensions. A candidate must average 4.0+ to receive an offer.
| Dimension | Description | Weight |
|---|---|---|
| Technical Proficiency | Quality of code, speed, knowledge of stack | 40% |
| Problem Solving | Ability to break down ambiguous problems | 30% |
| Communication | Clarity, English fluency, documentation | 20% |
| Culture Add | Mentorship potential, attitude, curiosity | 10% |
Conclusion
The goal of this interview is not to find a candidate who knows everything. It is to find a candidate who can learn anything, communicate clearly, and build maintainable software.
If you need help vetting talent or want to bypass this process entirely, Moydus provides pre-vetted, managed engineering teams ready to deploy in days.