The Scale AI Forward Deployed Engineer interview loop, round by round
Agent design with a cost constraint attached.
Thin public data. What is reported is an agent system-design round where token cost is part of the problem rather than an afterthought.
How we know this. One reported question and a census posting count. Far less corroboration than the Palantir or OpenAI pages; the stage list is partial rather than complete.
Who you meet
- Engineers
The rounds
1. Agent system design
What it grades
- Designing an insurance-claims agent: ingest claims, output an approval decision, using RAG
- Keeping LLM token cost under control as part of the design
Questions reported from this loop
- Design an insurance-claims agent that ingests claims and outputs an approval decision using RAG, while keeping token cost under control.
What is not on this page: the practice mapped to each round, and the list of what is not worth preparing for this loop. Both are in Rung.
Open this loop in Rung