Who this guide is for
- Mid-level to senior software engineers targeting roles at top-tier tech companies (FAANG, unicorns, well-funded startups).
- Engineers who know how to code but don't know how to interview.
- Prerequisites: Basic understanding of data structures and algorithms, and at least one year of professional engineering experience.
How technical interviews actually work
The interview process at tier-1 companies is highly standardized. Understanding the pipeline is the first step to beating it.
The 5-Stage Pipeline
Format: 30 min call. Evaluates: Communication, motivation, compensation alignment.
Format: 45-60 mins live coding. Evaluates: Algorithmic problem solving, clean code, communication.
Format: Half day. Coding, System Design, Behavioral, Role-specific. Evaluates: Deep technical depth and culture fit.
Format: Offline review. Evaluates: Interviewer feedback packets. Resolves split decisions.
Negotiation and team matching.
Round Type 1: Algorithmic Coding Interviews
What they test
Problem-solving under pressure, communication, code quality, and complexity analysis. They do not test memorization.
The 10 core patterns (know all of these)
Use when comparing or merging elements in a sorted array/string.
Use when optimizing contiguous subarrays or substrings.
Use when the search space is sorted or monotonic (O(log n)).
Use for tree/graph traversal, connected components, shortest paths.
Use when a problem has overlapping subproblems. Start with memoization.
Use when you need to explore all combinations with state pruning.
Use when you need repeated access to min/max or "top K" elements.
Use for "next greater element" or span-type problems.
Use for dynamic connectivity and cycle detection in graphs.
Use for fast, repeated range queries on arrays.
The 5-step problem-solving framework
Use this for every single problem, without exception:
Mistake: Writing code immediately.
Mistake: Skipping the obvious solution.
Mistake: Optimizing while coding.
Mistake: Going silent while typing.
Mistake: Assuming it works.
Practice all five steps out loud, with code that runs: free AI mock interviews for coding.
Round Type 2: System Design Interviews
What they test
Requirements gathering, architecture trade-offs, scalability reasoning, communication. They do not test whether you know the "perfect" architecture.
Key trade-offs you must be able to discuss
| Trade-off | Use A when... | Use B when... |
|---|---|---|
| SQL vs NoSQL | Need strict ACID, complex joins, financial data. | Need flexible schema, massive horizontal scale (feeds). |
| Sync vs Async | Client needs immediate feedback (login). | Task is heavy, caller doesn't need to wait (video encode). |
| Strong vs Eventual | Reading stale data is catastrophic (bank balances). | High availability is paramount (likes on a post). |
| Monolith vs Microservices | Small team, low complexity, easy deployment needed. | Multiple teams, independent scaling of components needed. |
Knowing the trade-offs is half of it; saying them under questioning is the other half. Here is how to practice system design interviews with AI, step by step.
Round Type 3: Behavioral Interviews
What they test
Past behavior as a predictor of future behavior, especially under pressure, in conflict, and at scale.
The 10 behavioral questions to prepare for
Have a STAR story prepared for each of these, and understand the intent behind the question:
- Tell me about a time you disagreed with your manager.
Tests: Do you have conviction? Can you handle conflict professionally? - Describe a project with unclear requirements.
Tests: Ambiguity tolerance, autonomy. - Tell me about a time you failed.
Tests: Self-awareness, learning agility, accountability. - Describe giving difficult feedback to a teammate.
Tests: Communication, empathy, psychological safety. - Tell me about your biggest technical achievement.
Tests: Calibration of your own impact and technical depth. - Describe influencing others without authority.
Tests: Leadership without title, consensus building. - Tell me about a time you had to balance speed vs. quality.
Tests: Engineering judgment, pragmatism. - Describe a time you mentored someone.
Tests: Investment in others, teaching ability. - Tell me about a time you had to learn something quickly.
Tests: Growth mindset, resourcefulness. - Describe a decision you made with limited data.
Tests: Decision-making under uncertainty, risk calculation.
Tell each story out loud before the real thing, ideally to someone who asks follow-up questions: a friend, or a behavioral mock interview with AI.
Round Type 4: Role-Specific Rounds
Frontend
- DOM manipulation
- Event loop & rendering
- React lifecycle/hooks
- CSS specificity
- Web performance
Backend
- Database indexing
- API design (REST/GraphQL)
- Caching strategies
- Message queues
- Auth patterns
ML Engineering
- Training pipelines
- Feature engineering
- Offline vs Online eval
- A/B testing
- Serving infrastructure
Your 6-week preparation plan
Assessment and foundations
Take a cold mock interview to identify baseline weaknesses. Study the 10 core algorithmic patterns (1 per day).
Algorithmic depth
Solve 2 timed problems per day using the 5-step framework. Practice verbal walkthroughs on every problem.
System design
Study 5 real architectures (Twitter, Uber, Stripe). Practice back-of-envelope estimation daily (10 mins, timed).
Behavioral prep
Build your story bank (document 8 stories in STAR). Practice answering the 10 core questions out loud, recorded.
Mock interviews
3 full mock interviews (Coding + System Design + Behavioral). Review feedback, identify top gaps, focus practice there.
Refinement
2 more full mock interviews. Polish story delivery, review edge case checklists, ensure complexity analysis is automatic.
Ready to start?
Interview preparation is a skill, and skills are trainable. The plan is in front of you. Use it.
Start your first mock interview