ATS Resume Expert | LinkedIn and FAANG+ Specialist | 350+ Clients, $37M in Offers Landed | Chief Career Strategist at Sareen Career Coaching
Give me 60 seconds and I’ll teach you how FAANG hiring actually works. Most candidates don’t understand that hiring is a business decision. If you can give a company the confidence that you can help them grow faster and streamline operations, you’ll get hired. Here is how these interviews actually work- 1. FAANG hiring is built around "role-specific calibration." Each open role has a calibration bar: → Specific years of experience. → Specific tech stacks or business environments. → Specific expectations for problem-solving at scale. Example: A "Software Engineer II" at Google needs a different bar than a "Backend Engineer" at a Series A startup. You can be brilliant, but if you’re not calibrated to the exact level they’re hiring for, you’ll get rejected even after good interviews. 2. Your resume is not for humans first. It’s for the Applicant Tracking System (ATS) – Front-load measurable impact: Not "worked on backend," but "Reduced API response times by 30%, handling 1 M+ requests/day." – Match keywords exactly: If the JD says "distributed systems," say "built distributed systems," not just "backend services." – One page. one narrative. one goal: Show ownership + scope + outcomes — clearly, not vaguely. 3. Interviewers are trained to assess ONLY 4 things. At companies like Amazon, Meta, and Google, structured interviewing focuses on: – Technical Competence (Can you do the job?) – Problem-Solving Ability (Can you handle new challenges?) – Leadership and Ownership (Will you raise the bar?) – Culture Fit (Will you thrive here long-term?) Every answer you give is silently graded against these pillars. 4. Behavioral interviews are gated rounds, not just “nice to have.” If you fail the behavioral, you won’t get the offer — no matter how good your technical rounds are. – At Amazon: You must show Leadership Principles in action. – At Google: You must show Googliness — humility, collaboration, resilience. Examples you need ready: – A time you failed and recovered. – A time you disagreed with your manager/team and what you did. – A project where you scaled or innovated beyond your initial role. Final decision = "Hire Bar" + "Risk profile." Even if you do well in interviews, decision makers assess: – Was the bar met on technical, behavioral, and cultural axes? – Are there red flags that introduce too much risk? (eg, poor collaboration feedback, inconsistent behavior.) One strong interview cannot save you. One unclear answer can cost you. FAANG hiring is about knowing the invisible rules and playing the game better. ✅ Get your resume tuned for impact and visibility. ✅ Learn how to pass calibration, not just technical screens. ✅ Prepare your STAR stories and tie them to leadership + outcomes. ✅ Understand how hiring decisions are actually made. P.S. If you are looking to break into a high-paying tech role at Amazon, Meta, Google, or other FAANG+, DM me, and let’s build a sure-shot strategy.
Wow, this was a lot of value, Sanyam. Your point on behavioral rounds and structuring for the ATS are key.
Breaking Tech’s Pedigree Barriers | 308 GRE → UC Irvine → Google | Career Coach | Helping Average Students Break Into Global Tech Careers | 3x Published Researcher
2dI bombed my Meta interview in 13 minutes because I didn't understand this. Knew the algorithms. Practiced LeetCode for months. But couldn't articulate my projects in terms of "scale" and "impact." Google interview? Different story. Talked about optimization affecting millions of users. Same skills, better framing. The game has rules. Learn them or lose.