Start by understanding the interview structure — data structures and algorithms, system design (for senior roles), and behavioral rounds. Build a preparation timeline of 8–12 weeks, practice coding daily on platforms like LeetCode, solve problems by topic, and simulate real interview conditions. Doing a mock interview with someone who has already cleared these rounds, such as an engineer working at a top tech company, can significantly sharpen your readiness.

FAANG interviews demand depth, not just familiarity. Focus on medium and hard DSA problems, learn to communicate your thought process out loud, practice system design if you're interviewing for SDE2 or above, and prepare structured behavioral answers using the STAR method. Since the bar is high, getting interview preparation and tips from someone currently working at one of these companies helps you understand what interviewers actually evaluate.

Expect coding questions on arrays, strings, trees, graphs, and dynamic programming, followed by design and leadership/behavioral questions depending on the level. Questions are often more about how you reason through edge cases and optimize than about getting the perfect answer fast. Reviewing commonly asked FAANG interview questions and practicing them with feedback — rather than alone — is one of the fastest ways to improve.

Yes. Most candidates fail not because they don't know the solution, but because they freeze, go silent, or fail to structure their thinking. A mock interview replicates real pressure, exposes gaps in your communication, and gives you actionable feedback. Doing at least 2–3 mocks before your actual interviews is widely recommended, especially for FAANG-level roles.

A strong review checks for quantified impact, clear formatting, ATS compatibility, and role-relevant keywords. Many candidates list responsibilities instead of achievements — a proper resume review fixes that by rewriting bullet points around measurable outcomes. While AI tools and ChatGPT prompts can help with a first pass, human feedback from an engineer at a top company catches issues AI misses, like how a recruiter or hiring manager will actually perceive your experience.

LinkedIn resume review threads can give general feedback, but they're inconsistent — you'll get opinions rather than structured advice, and posting your resume publicly has privacy downsides. A dedicated resume review from a working software engineer at a company like Amazon gives you targeted, honest feedback on how to position yourself for the roles you want.

If you're applying to competitive roles — FAANG, product companies, or internships with high selectivity — a resume review service from someone who has actually sat on the hiring side of the table is worth it. Generic services often just fix grammar; a review from a practicing software engineer focuses on whether your projects, impact, and skills match what top companies screen for.

Common trigger points include choosing between service-based and product companies, deciding when to switch jobs, preparing for a FAANG jump, picking between frontend/backend/full-stack paths, or feeling stuck in your current role. Early-career engineers and final-year students benefit most, since decisions made in the first few years compound over time. A 1:1 career guidance session with someone who has made those transitions helps you avoid expensive mistakes.

For freshers, the priority order is: strong DSA fundamentals, 150–250 well-understood LeetCode-style problems, core CS subjects (OS, DBMS, OOPs, networks), and at least one solid project you can explain in depth. College placements and off-campus drives both reward consistent practice, and a mock interview or two before the season starts gives you a real sense of where you stand.

System engineer roles (commonly at services companies in India) usually test aptitude, basic programming, and CS fundamentals, while software engineer interviews at product companies go deeper into DSA, problem-solving, and system design. Know which type of company you're targeting — your software engineer interview preparation should be much more rigorous for product-based roles, and understanding that difference early shapes how you prepare.