Show us what you can build.
The on-site careers application form has been removed. Use the self-check below, then contact us through getstarted with your role, GitHub, and video links.
Skills & knowledge check.
No submission happens here. Use this self-check to prepare, then send your links through getstarted for the AI Agent Developers role.
- 01
You need an agent to run a multi-step task reliably in production. What matters most?
- 02
What does retrieval-augmented generation (RAG) add over a base LLM?
- 03
A paid-ads automation must adjust bids hourly from performance data. Cleanest approach?
- 04
You prototyped fast with AI codegen. Before it ships to production, you…
- 05
Serving thousands of agents on LLMs, your biggest cost/latency lever is usually…
- 06
You need to ship a risky change without blocking the team. Best practice?
- 07
An agent calls a tool that sometimes times out and is NOT idempotent. Safest design?
- 08
Your RAG system retrieves relevant docs, but answers are still stale. Most likely fix?
- 09
Hybrid search (vector + keyword) usually beats pure vector search because…
- 10
A high-volume classification step is expensive on a frontier model. First thing to try?
- 11
Your agent browses untrusted web content, then takes actions with its tools. Biggest risk?
- 12
An automated bidding loop adjusts ad budgets from ROAS. What's non-negotiable?
- 13
Long agent runs degrade as context fills with history. Best practice?
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