Software Developer III, Infrastructure, Google Cloud Business Platforms

Google

Let's simulate a coding interview scenario. I'd like you to solve a problem and articulate your thought process as you go. Imagine you're given an array of integers. Your task is to write a function that finds the length of the longest strictly increasing subsequence in that array. A strictly increasing subsequence is a sequence of numbers from the array such that each number is greater than the previous one, and their original order in the array is maintained. For example, in the array [1, 3, 2, 4, 5], one possible increasing subsequence is [1, 2, 4, 5], and the longest increasing subsequence is [1, 2, 4, 5], which has a length of 4. Another possible increasing subsequence is [1, 3, 4, 5] which has length of 4. Your function should return 4 in this case. Another example is [10, 9, 2, 5, 3, 7, 101, 18]. The longest increasing subsequence is [2, 3, 7, 18], which has a length of 4. Your function should return 4. Can you describe your approach and then implement the function? Consider edge cases, like an empty array or an array with only one element. How would your approach handle those? What is the time and space complexity of your solution?

Google

Let's design a rate limiter for an API. The rate limiter should: Limit the number of requests a user can make to an API within a given time window. Support different rate limits for different users or API endpoints. For example, a free tier user might be limited to 10 requests per minute, while a premium user can make 100 requests per minute. Similarly, some API endpoints might have lower rate limits than others due to resource constraints. Be highly performant to avoid adding significant latency to API requests. Be scalable to handle a large number of users and API requests. Be reliable and prevent accidental overloads that could cause service disruptions. Describe the architecture, algorithms, and data structures you would use to implement such a rate limiter. Consider the following: How would you store the rate limit counters for each user or endpoint? What algorithm would you use to determine whether a request should be allowed or throttled? How would you handle distributed rate limiting across multiple servers? How would you ensure the rate limiter is resilient to failures? As an example, imagine a scenario where a social media platform wants to prevent users from spamming their API with excessive requests to post updates. The platform has millions of users and thousands of API endpoints. Some users pay for premium access with higher request limits. How would you design a robust and efficient rate limiter to handle this scale and these varying requirements?

Google

Tell me about a time you had to work with a signed contract. Describe the situation, your role, and the outcome. What were the key clauses or provisions that were most relevant to the situation? What challenges, if any, did you face in interpreting or adhering to the contract terms? How did you ensure that your actions were in compliance with the contract, and what steps did you take to mitigate potential risks or disputes? For example, consider a scenario where you were managing a project with a vendor, and the contract outlined specific deliverables, timelines, and payment terms. A conflict arose when the vendor failed to meet a critical deadline, potentially impacting the project's overall timeline and budget. How did you leverage the contract to address the issue, protect your company's interests, and find a resolution that was fair to both parties? Or, imagine you were involved in a negotiation where the other party wanted to change certain terms after the contract was signed. How did you handle the situation, ensuring that any modifications were properly documented and agreed upon by all parties involved? What did you learn from this experience, and how has it influenced your approach to working with contracts in subsequent projects or situations?