Technical interview preparation is poorly documented. Most guides tell you to "practice LeetCode" without explaining why, which types of problems matter for which roles, or how to structure the five or six hours before an interview. This guide covers what to prepare, in what order, and how to handle the parts that aren't about algorithms.
What technical interviews actually test
Technical interviews at most companies test four distinct things, usually in separate rounds:
- Coding / DSA - data structures and algorithms, problem-solving under time pressure
- System design - designing systems at scale: APIs, databases, distributed components, trade-offs
- Behavioral / experience - past projects, how you've handled technical challenges and team situations
- Domain knowledge - specific to the role: infrastructure, ML, frontend performance, security, etc.
The ratio varies significantly by seniority. Junior and mid-level engineers spend most of their interview process on coding rounds. Senior and staff engineers spend more time on system design and behavioral. The mistake most candidates make: over-preparing for coding and under-preparing for system design at senior+ levels.
Coding interview preparation
If you have 4+ weeks: Work through 75–100 LeetCode-style problems covering these patterns: arrays/strings, hash maps, two pointers, sliding window, binary search, linked lists, trees/graphs (BFS/DFS), dynamic programming, and heaps. Understand the time and space complexity of every solution you write - not just whether it passes.
If you have 1–2 weeks: Focus on the patterns most commonly asked by companies you're interviewing at. For FAANG and large tech companies, tree/graph traversal, dynamic programming, and string manipulation are the highest-frequency categories. For startups and mid-size companies, the focus is often more on practical data structures and less on advanced DP.
If you have 2–3 days: Pick 20 medium-difficulty problems covering arrays, trees, and graphs. Prioritize speed and pattern recognition over correctness - knowing which approach to start with is more important than implementing perfectly in a first pass.
During the interview itself:
- Think out loud from the start. Interviewers want to see how you reason, not just your output
- Ask clarifying questions before coding - edge cases, input constraints, expected output format
- Start with a brute-force approach and then optimize, rather than jumping straight to the optimal solution
- Write readable code with meaningful variable names - interviewers are humans who have to follow your logic
Recruiter perspective
According to GitHub's Octoverse report, technical interviews at the companies hiring the most engineers have increasingly shifted toward assessing practical problem-solving and system design skills over pure algorithm recall - particularly for senior roles where production impact is the evaluation criterion.
System design preparation
System design rounds evaluate your ability to think through a system at scale: components, data models, APIs, consistency trade-offs, failure modes, and scaling decisions. Unlike coding rounds, there's no single correct answer - the evaluation is on your reasoning process.
Core topics to understand:
- Horizontal vs vertical scaling - when each applies and the trade-offs
- SQL vs NoSQL - when to use each, CAP theorem basics
- Caching strategies - when to cache, cache invalidation, CDN vs application cache
- Message queues - when to use async processing, at-least-once vs exactly-once delivery
- Load balancing - types (L4 vs L7), session affinity, health checks
- Database indexing - how indexes work, when they help and hurt
- API design - REST vs gRPC, pagination, versioning, rate limiting
- Distributed system basics - consistency vs availability trade-offs, distributed transactions
Practice format: Pick a known system (URL shortener, rate limiter, notification system, search autocomplete, ride-sharing backend) and design it from scratch in 45 minutes. Start with requirements clarification, sketch the high-level components, then drill into specific pieces where trade-offs exist.
For senior roles, the ability to discuss trade-offs explicitly - "I'm choosing PostgreSQL here over Cassandra because our write volume is low and we need strong consistency for billing records" - is what separates a passing design from a strong one.
Behavioral interview preparation
Behavioral rounds test how you've handled real situations: technical disagreements, production incidents, cross-functional conflicts, ambiguous requirements, and decisions under uncertainty.
Use the STAR format: Situation → Task → Action → Result.
Prepare 5–7 stories covering:
- A technical decision you made with incomplete information and how it played out
- A production incident you owned: what happened, how you diagnosed it, what you changed
- A time you disagreed with a technical direction and how you handled it
- A project where you had to influence without authority
- A time you failed technically and what you learned
Keep each story to 2–3 minutes. The result must be specific - "we reduced the incident rate by 70% in the following quarter" beats "things improved significantly."
The connection between behavioral preparation and how you present your past work also shows up in your resume. Strong resume bullets and strong behavioral stories draw from the same pool of real outcomes. See how to write a software engineer resume for how to document those outcomes before the interview.
Company-specific preparation
Two hours of company-specific research before each interview changes the quality of both your questions and your answers:
Engineering blog: Most tech companies publish their engineering blog. Read 2–3 recent posts - they tell you what technical problems the team is actually solving. If you reference a specific post in your system design ("your blog post on migrating to event-driven architecture is similar to a problem I worked on..."), it signals genuine interest and domain familiarity.
JD language: The job description's required skills are the vocabulary the interviewer is listening for. If the JD says "high-throughput data pipelines," use that phrase when describing relevant experience. Don't make them translate between your vocabulary and theirs.
Recent news: Funding rounds, product launches, acquisitions, or engineering reorgs change what the team needs. A company that just raised Series B is likely building - they want engineers who can ship fast. A post-IPO company is likely scaling - they want engineers who've operated production systems.
On the day before
Don't cram. Reviewing 20 new problems the night before adds noise without adding signal. If you haven't solved a problem type in your preparation, you won't solve it in 12 hours.
What to do instead:
- Review 5–10 problems you've already solved - reinforce pattern recognition
- Review your behavioral stories out loud - saying them is different from thinking them
- Set up your environment: stable internet, working headset, clean screen share, IDE ready
- Sleep. Cognitive performance on algorithmic problems drops measurably with sleep deprivation
Tracking interviews as part of your search
A structured job search means tracking where you are in each process: which companies you've applied to, which have advanced to technical rounds, which are waiting on callbacks. Hire.monster's tracker (Kanban + Table + Calendar) lets you manage this across your full pipeline - not just applications but interview stages. See how to track job applications without losing candidates for the workflow.
Key takeaways
Senior engineers over-prepare for coding and under-prepare for system design
LeetCode preparation is weighted too heavily in most senior engineer interview prep. For roles where system design rounds exist (typically 5+ years experience), the system design round carries as much or more weight - and has a much wider performance spread among candidates.
Thinking out loud is the evaluation, not just the solution
Interviewers are assessing reasoning under uncertainty, not output under certainty. Starting with a brute-force approach and narrating the optimization process is more impressive than 5 minutes of silence followed by an optimal solution. The process is the interview.
Behavioral preparation draws from the same material as resume writing
Your resume bullets and your behavioral stories are the same outcomes, described in different formats. Preparing both in parallel - writing outcomes for the resume, then practicing them as verbal narratives for behavioral rounds - is the most efficient use of preparation time.
Frequently asked questions
How long does it take to prepare for a FAANG technical interview?
4–8 weeks of structured daily preparation (1–2 hours/day) for candidates without recent interview experience. The variation depends on how long it's been since you've done competitive programming problems and whether you've prepared for system design before. For staff+ interviews, add 1–2 weeks of system design focus.
Is LeetCode Premium worth it?
For interviews at specific companies - yes, if that company's questions are listed. LeetCode Premium's company-tagged question sets are accurate for FAANG. For most startups and mid-size tech companies, the benefit is smaller. Free LeetCode with a structured problem list is sufficient for most interview preparation.
Should I do mock interviews?
Yes, at least 2–3 before your actual interviews. Coding on a screen-shared whiteboard while explaining your reasoning is a skill separate from problem-solving ability. Most candidates perform meaningfully better after a few mock sessions simply because the format feels less unfamiliar. Pramp, interviewing.io, and peer practice with friends are all viable.
What if I blank on a problem?
Say it out loud: "I'm not immediately seeing the optimal approach - let me think through a brute force first." Then write the brute force. Most interviewers will give hints if you're visibly working through the problem rather than sitting silently. Asking for a hint explicitly ("Can I get a nudge on the data structure to consider?") is also acceptable and better than freezing.
Do system design interviews have a right answer?
No. System design interviews have better and worse answers based on how well your design addresses the requirements, how clearly you articulate trade-offs, and how realistic your estimates are. Interviewers are evaluating reasoning quality, not whether you arrived at their mental model of the system.
Bottom line
- Senior engineers: prepare system design as seriously as coding - the ratio of evaluation weight is higher
- Behavioral stories: 5–7 scenarios covering decisions, incidents, disagreements, and failures
- 2 hours of company-specific research before each interview - engineering blog, JD language, recent news
- Day before: review solved problems, practice behavioral stories out loud, no cramming new material
- Track all your interviews - stages, contacts, dates - in one place so nothing falls through
Find roles worth preparing for: hire.monster/jobs.