Role: Product Intern <> Verdict: Selected R1 - DSA (45M) • 4Sum (O(n²)) • LRU Cache R2 - Everything (45M → 1H30M) Behavioral: • What drives you to build products? • Shipping under deadline pressure Deduplication System Deep Dive: Took my project to production scale. • 10k+ event types, auto TTL configuration • Cache management with skewed observation windows • Metrics for dedup performance • Cache failure recovery strategies • Multi-tenant configuration system Designed YAML config: • TTL modes: Fixed, Adaptive, Custom • Cache type selection • boolean isDuplicate(event E) Coding: Implement adaptive TTL algorithm in Python. • Event frequency tracking • Dynamic TTL adjustment • Self-healing, stable DSA: Equation validation (A==B, A!=B) • O(N) + O(N²) space → rejected • Union-Find → "optimize more" • Path compression + union by rank → approved R3 - C&T (30M) • Why not campus? • Dream company? • Other interviews? • HPE internship decision • AI impact on recruiting Ended discussing chole kulche.