Interview - OCI | IC3 | USA

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oci
SDE IIUSA
August 28, 202513 reads

Summary

I recently completed a challenging four-round interview process for an IC3 software engineering role at OCI in the USA, which thoroughly assessed my technical coding, system design, and behavioral skills.

Full Experience

I recently went through an intensive interview process for an IC3 role at OCI in the USA. The entire experience was structured across four distinct rounds, each designed to evaluate a different aspect of my software engineering capabilities. It felt quite comprehensive, covering everything from core algorithms to complex system architecture.

Round 1: Technical Coding (HackerRank)

This round was a HackerRank coding challenge focused on Greedy Algorithms and Heap data structures. The specific problem involved minimizing the total cost of an array of prices using a given number of tokens. It was a good test of my algorithmic problem-solving and optimization skills.

Round 2: Behavioral Interview

The second round was purely behavioral. It consisted of scenario-based questions, similar to Amazon's leadership principles interviews. The focus was on my past work experience, projects I've handled, and the decision-making processes I employ. I was asked to discuss situations where I demonstrated leadership principles.

Round 3: System Design

This round was a deep dive into system design. The core problem was to design a Distributed Rate Limiter. The discussion revolved around ensuring scalability, understanding distributed systems concepts, evaluating various trade-offs, and architectural thinking. We covered topics like load balancing, data consistency, and performance optimization.

Round 4: Advanced Coding

The final round was an advanced coding challenge. I was tasked with implementing an LFU (Least Frequently Used) Cache. This problem thoroughly tested my knowledge of data structures, cache replacement algorithms, and my ability to achieve optimal time and space complexity, particularly in balancing frequency tracking with efficient operations.

Key Observations

  • Every single round, not just the dedicated behavioral one, included questions related to leadership principles, mirroring Amazon's interview style.
  • The technical depth was significant, ranging from intricate algorithmic optimization to high-level system architecture, effectively testing both my coding prowess and my system-level thinking.
  • The difficulty felt progressive, with each round building upon different technical skills: algorithms, then behavior, then systems, and finally advanced data structures.

Overall, the process was very well-structured and comprehensive, effectively evaluating both my technical expertise and my potential for leadership within a software engineering context. Each round clearly had a specific purpose in assessing different facets of my competency.

Interview Questions (3)

Q1
Minimize Total Cost with Tokens
Data Structures & Algorithms

Given an array of prices and M tokens, use all tokens to reduce costs and return the minimum total cost.

Q2
Design Distributed Rate Limiter
System Design

Design a Distributed Rate Limiter. The discussion focused on scalability, distributed systems concepts, trade-offs, and architectural thinking, covering areas such as load balancing, data consistency, and performance optimization.

Q3
Implement LFU Cache
Data Structures & Algorithms

Implement LFU (Least Frequently Used) Cache. This problem required demonstrating strong understanding of data structures, cache replacement algorithms, and aiming for optimal time and space complexity while balancing frequency tracking with efficient operations.

Preparation Tips

To prepare for interviews like these, I focused on several key areas:

  • Extensively practicing greedy algorithms and operations involving heaps.
  • Thoroughly reviewing various system design patterns, especially for distributed systems.
  • Implementing classic cache replacement algorithms from scratch, such as LRU and LFU, to solidify my understanding.
  • Preparing my behavioral stories using the STAR format to effectively address leadership principle questions.
  • Practicing articulating my technical decisions and explaining trade-offs clearly and concisely.
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