The company is really positioned well. The core flexible ontology concepts in Foundry and Gotham are incredible tools in an AI-driven world where a simple schema isn't enough.
There are also lots of great and really motivated people here. Conflict is rare, and the company manages to maintain a feeling of constant urgency. You're always working on the most important thing.
You always have more work than you can complete, so you never get to feel done.
Management is largely engineers that have been promoted up, but it ends up feeling like no one knows what they are doing at the management level. Management has a knack for not communicating, so you often get different stories and have trouble putting together the truth.
For a long time, folks were strung along with promised raises that never came.
Company policy changes almost on a dime. Everything is focused around constant change, and mature products are looked at as chores to get rid of; nothing gets to be finished.
Had a recruiter call covering general questions, followed by a phone screen. The screen featured a LeetCode-type problem: compute the price of a stock portfolio for every day it remains active.
The recruiter initially scheduled and conducted my first interview. This was a phone-based behavioral interview where we discussed my background, experiences, and potential fit for the role.
One phone screen. It included generic behavioral questions, followed by a technical assessment. The technical portion involved parsing data and efficiently storing and manipulating it to create an output. This required knowledge of hash maps and sor
Had a recruiter call covering general questions, followed by a phone screen. The screen featured a LeetCode-type problem: compute the price of a stock portfolio for every day it remains active.
The recruiter initially scheduled and conducted my first interview. This was a phone-based behavioral interview where we discussed my background, experiences, and potential fit for the role.
One phone screen. It included generic behavioral questions, followed by a technical assessment. The technical portion involved parsing data and efficiently storing and manipulating it to create an output. This required knowledge of hash maps and sor