1. What is a Software Engineer?

At Glean, the role of a Software Engineer is central to the company's mission of creating the "Google for the workplace." Glean builds an AI-powered work assistant that connects across all of a company's applications to help employees find exactly what they need. In this role, you are not just building standard CRUD applications; you are solving complex challenges related to enterprise search, knowledge graphs, generative AI, and data ingestion at scale.

You will work on high-impact projects that directly affect the user experience, such as optimizing search relevance, building connectors for third-party apps (like Slack, Jira, or Salesforce), or architecting the infrastructure that powers real-time indexing. The engineering culture at Glean is fast-paced and technically rigorous. Engineers here are expected to own their features from conception to deployment, navigating the ambiguity typical of a high-growth startup environment while maintaining the code quality expected of a top-tier tech firm.

2. Common Interview Questions

These questions are based on real interview experiences from candidates who interviewed at this company. You can practice answering them interactively on Dataford to better prepare for your interview.

3. Getting Ready for Your Interviews

Preparation for Glean requires a shift in mindset. While standard algorithmic fluency is required, the company places a heavy premium on practical engineering speed and startup adaptability. You need to demonstrate that you can build working software quickly without getting bogged down in bureaucracy.

Key Evaluation Criteria

Algorithmic Problem Solving – You must demonstrate the ability to solve complex data structure problems efficiently. Interviewers look for clean, bug-free code produced at a rapid pace, often testing your ability to handle edge cases in real-time.

Practical Coding Ability – Unlike many big tech firms that stick solely to LeetCode, Glean often tests your ability to build a mini-application or feature from scratch. You are evaluated on code organization, modularity, and how well your solution runs.

System Design & Architecture – For mid-level and senior roles, you will be assessed on your ability to design scalable systems. You need to show deep understanding of trade-offs, particularly regarding data consistency, API design, and high-availability infrastructure.

Startup Mindset & Culture Fit – Glean values engineers who are proactive and resilient. Interviewers assess whether you thrive in a high-ownership environment or if you rely heavily on existing "big company" infrastructure. You must show a willingness to move fast and tackle undefined problems.

4. Interview Process Overview

The interview process at Glean is known to be rigorous and can be lengthy compared to other startups. It generally begins with a recruiter screen, followed by one or two technical phone screens. These initial screens are usually algorithmic in nature but can sometimes involve practical discussions about your past projects.

If you pass the screening stage, you will move to the "onsite" loop (usually virtual). This is an intense series of rounds that typically includes advanced algorithmic coding, a system design session, a behavioral round with a Hiring Manager, and—most notably—a practical coding assignment. This assignment (often 2 hours long) is a distinguishing feature of Glean's process, designed to see if you can translate logic into a working application under time pressure. The bar is high; candidates are expected to produce a significant amount of working code during these sessions.

The timeline above illustrates the typical flow from application to final decision. Note the Practical/Project Round during the onsite phase; this is often the "make or break" step for many candidates. Plan your energy accordingly, as the onsite can feel like a marathon, often lasting 4 to 5 hours in total.

5. Deep Dive into Evaluation Areas

Glean’s technical bar is comparable to top-tier tech companies, but with a specific twist towards practical implementation. You should prepare for the following specific areas.

Data Structures & Algorithms (DSA)

This is the foundation of the early rounds. Expect questions that range from LeetCode Medium to Hard. You are expected to drive the conversation, explaining your space and time complexity clearly.

Be ready to go over:

• Graph Algorithms – DFS/BFS traversals are very common (e.g., finding paths, connected components).
• Arrays and Matrices – Manipulation of 2D grids and logic puzzles.
• Heaps and Priority Queues – merging data streams or managing sorted data.
• Advanced concepts – Dynamic programming and recursion appear occasionally, but core data structure manipulation is prioritized.

Example questions or scenarios:

• "Solve a variation of the Connect 4 game, handling win conditions efficiently."
• "Implement a solution similar to 'Rotate Image' on LeetCode."
• "Merge multiple sorted arrays or lists using a heap."

The Practical Coding Assignment

This is often a 2-hour session where you are asked to build a small project or a complex feature. This is not a standard algorithm puzzle; it is a test of your software engineering craftsmanship.

Be ready to go over:

• Code Organization – How you structure classes, files, and functions.
• Speed and Accuracy – You need to produce a "grueling amount of code" (as described by past candidates) in a short time.
• Testing – Writing test cases for your own code as you go.

Example questions or scenarios:

• "Build a working backend for a specific game or service."
• "Implement a simplified version of a search indexer."

System Design (LLD & HLD)

For experienced candidates, this round assesses how you architect solutions.

Be ready to go over:

• API Design – Defining clean, RESTful endpoints and request/response structures.
• Scalability – How to handle high throughput and data ingestion.
• Database Schema – Designing tables for specific use cases (e.g., a social feed or document storage).

Example questions or scenarios:

• "Design an API for a file storage system."
• "How would you architect a system to crawl and index data from Slack?"