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cortex

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Cortex is a software company that provides an internal developer portal and service catalog platform, helping engineering teams track, manage, and improve the quality of their microservices and software systems. It is known for enabling organizations to enforce engineering standards and gain visibility into service ownership and reliability.

3 interview notes · updated Jul 2026

cortex·Software Engineer·Technical Phone Screen

Jun 2026
Got a coding question at Cortex that was basically a tree traversal problem dressed up as an HR tool. Pretty straightforward if you've done BFS before, but the CSV parsing part tripped me up for a minute.
  • Given a CSV file with employee name, title, department, and manager name columns, build the company's org hierarchy and print employees level by level: the root (CEO or whoever has no manager) on line one, their direct reports on line two, and so on down the tree using BFS.

“I knew it was BFS the second they said 'level by level' but I fumbled the setup.”

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cortex·Software Engineer·Technical Phone Screen

May 2026
Two practical coding tasks for a Software Engineer role at Cortex. Nothing too exotic, but the follow-up discussion on the first one pushed into real engineering territory, and the org chart problem had enough edge cases to keep things interesting.
  • Make a GET request to an HTTP endpoint that returns a JSON list of transit stops, then print each stop's name and description on one line.
  • Following the API task: what would you change to make this production-ready? Think about error handling, retries, timeouts, logging, schema changes, pagination, and testing.
  • Given a CSV of employees with their manager's name, print the org chart with each level indented by two spaces, and direct reports sorted alphabetically under each manager.

“Pretty straightforward fetch-and-parse.”

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cortex·Software Engineer·Technical Phone Screen

Apr 2026
Cortex gave me a practical Java coding exercise using a real public transit API, then pivoted into a surprisingly deep system design conversation about what it would take to make that same code production-ready. The coding part was fine; the follow-up is where it got interesting.
  • Given a pre-written Java API client for a public transit service, parse the JSON response and extract specific fields like stop name and description. You can look up libraries during the exercise.
  • What changes would you make to turn this code into something production-ready? Walk through error handling, retries, timeouts, schema validation, observability, configuration, and testability.

“The fact that they let you look things up sounds chill until you realize you're burning time googling Jackson vs Gson while they're watching.”

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