Software Engineer III, Platforms Infrastructure Engineering

Google

Global technology company that develops internet-related services and products.

Sunnyvale, CA, USA • Kirkland, WA, USA • Pittsburgh, PA, USA…

$141,000 - $202,000

Backend

Mid-Level Software Engineer

In-Person

5,000+ Employees

2+ years of experience

Enterprise SaaS

Description For Software Engineer III, Platforms Infrastructure Engineering

Google is seeking a Software Engineer III to join their Platforms Infrastructure Engineering team, a critical role that helps shape how billions of users interact with Google's services. This position offers an opportunity to work on large-scale systems and next-generation technologies that extend well beyond web search. The role requires expertise in software development, data structures, and algorithms, with opportunities to work across the full technology stack.

The Technical Infrastructure team is responsible for building and maintaining the architecture that powers Google's extensive product portfolio. This includes developing and maintaining data centers, creating next-generation platforms, and ensuring networks operate at peak performance. The role combines hands-on technical work with collaborative responsibilities such as participating in design reviews and code reviews.

The position offers a competitive compensation package ranging from $141,000 to $202,000, plus bonus, equity, and comprehensive benefits. The ideal candidate will have at least 2 years of experience in software development and a strong foundation in data structures and algorithms. They should be versatile, display leadership qualities, and be enthusiastic about tackling new challenges across the full-stack.

Working at Google means joining a team that's proud to be the "engineers' engineers," with a culture that embraces taking things apart and rebuilding them to make them better. The role provides opportunities to work on projects critical to Google's needs, with the flexibility to switch teams and projects as both the engineer and the fast-paced business grow and evolve.

This position is perfect for someone who wants to make a significant impact on technology that affects billions of users while working alongside some of the industry's best engineers. The role offers growth opportunities, technical challenges at massive scale, and the chance to work on cutting-edge technology in areas including distributed computing, large-scale system design, networking, data storage, security, and artificial intelligence.

Last updated 3 days ago

Responsibilities For Software Engineer III, Platforms Infrastructure Engineering

Write product or system development code
Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies
Review code developed by other developers and provide feedback to ensure best practices
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality

Requirements For Software Engineer III, Platforms Infrastructure Engineering

Java

Python

Kubernetes

Bachelor's degree or equivalent practical experience
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting
2 years of experience with data structures or algorithms in either an academic or industry setting
English proficiency

Benefits For Software Engineer III, Platforms Infrastructure Engineering

Medical Insurance

401k

Bonus
Equity
Benefits package

Google

Global technology company that develops internet-related services and products.

Sunnyvale, CA, USA • Kirkland, WA, USA • Pittsburgh, PA, USA…

$141,000 - $202,000

Backend

Mid-Level Software Engineer

In-Person

5,000+ Employees

2+ years of experience

Enterprise SaaS

Google

Find the length of the longest strictly increasing subsequence in an array of integers. Describe your approach and its complexity, considering edge cases. Provide examples to illustrate your solution. How would the approach handle edge cases such as an empty array, or an array with only one element, impacting complexity and efficiency of the approach taken? What is the time and space complexity of your solution? Provide the results for the sample arrays `[1, 3, 2, 4, 5]` and `[10, 9, 2, 5, 3, 7, 101, 18]` to ensure proper functionality of your function, by returning 4 in both test cases. This will ensure a good understanding of increasing subsequences in a sequence of numbers in an array, while testing for a well-defined approach that is efficient to use with a variety of test data sets. This showcases proficiency in algorithmic thinking and problem-solving skills by handling an array of integers to find the longest length of a strictly increasing subsequence while addressing edge cases that may arise from the sample data set used in this test case. It shows a deep understanding of the problem, as well as the ability to articulate, plan and design a proper solution to provide the right output for each test case provided in this simulated scenario. This emphasizes the importance of code quality and readability, alongside accuracy of the algorithm to assess for proficiency in the related subject matter of programming and computer science principles that are essential for the role being assessed during this interview process. This would ensure your approach is robust and adaptable to different datasets, showcasing a solid understanding of data structures and algorithms and best practices for writing clean and efficient code for software development tasks that require these skills on the job daily in a multitude of projects throughout different teams as well as departments that handle data sets of different formats for various software being implemented across platforms where these are deployed for specific functions that relate to them to facilitate the development process for various user needs and requirements in the long run over the years in the industry with current trends using similar coding techniques at this stage or level of sophistication regarding different paradigms applicable here according to what can be adopted as far as current resources permit at any given point along the timeline for improvements that are needed in relation with available funds at the moment etcetera, to keep things viable for longer-term sustainability within market forces at this juncture given whatever competing forces might impact profitability.

Data Structures & AlgorithmsHard

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?

Arrays

Dynamic Programming

Google

How would you design a thread-safe LRU cache with O(1) get and put operations?

System DesignHard

Let's design a cache. Consider the following requirements: Basic Functionality: Implement a cache with put(key, value) and get(key) methods. Eviction Policy: Implement an LRU (Least Recently Used) eviction policy. When the cache is full, the least recently accessed item should be evicted to make space for the new item. Thread Safety: Ensure the cache is thread-safe to handle concurrent access from multiple threads. Generics: The cache should be able to store any type of key and value (using generics). Time Complexity: get and put operations should have an average time complexity of O(1). Example Usage: Cache cache = new Cache(5); // Cache with capacity 5 cache.put(1, one); cache.put(2, two); cache.get(1); // Access key 1, moves it to the most recently used cache.put(3, three); cache.put(4, four); cache.put(5, five); cache.put(6, six); // This will evict key 2 (LRU) System.out.println(cache.get(2)); // Output: null (because it was evicted) Discuss the data structures you would use, the implementation details for each method, and how you would address thread safety.

Database Problems

Arrays

Strings

Two Pointers

Stacks

Binary Search

Sliding Windows

Linked Lists

Trees

Recursion

Graphs

Dynamic Programming

Greedy Algorithms

Bit Manipulation

Google

Where do you see yourself in 5 years?

Behavioral

Where do you see yourself in 5 years?

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