LLM & GenAI technical tests: prepare effectively
Prepare for LLM, RAG, or prompt engineering tests: free Ganloss challenges, auto grading, profile badges tied to your AI projects.
AI interviews shift away from pure LeetCode toward RAG, agents, prompts, and pipeline debugging. Ganloss offers 17 role-oriented challenges linked to your candidate portfolio.
What recruiters test in 2026
Retrieval and chunking, prompt injection, eval metrics (faithfulness), system prompts, agents and tool calling, MLOps monitoring, cost/latency trade-offs, and Python data tasks (chunking, cosine similarity, parsing tool calls). They check delivery experience, not paper recitation.
Ganloss track (17 challenges)
9 quizzes (RAG, security, eval, agents, infra), 5 written prompts (chunking, agent memory, monitoring, guardrails), 3 Python exercises. Score ≥ 70/100 passes. “Validated” badge at 4 tests, “expert” at 8.
Prep plan (~3 hours)
1) Review a personal or work RAG/agent project. 2) Run quizzes to calibrate. 3) Write answers on chunking and monitoring. 4) Code chunk_text, cosine_similarity, extract_tool_name. 5) Save badges on your public profile.
During the test
Explain your choices in the dedicated field — Ganloss recruiters see reasoning, not only score. Stay on tab; focus changes are logged (light proctoring).
Keep exploring
FAQ
- Do I need expert Python to pass?
- No. Most items are quizzes or written answers. The three Python tasks are junior/mid (chunking, cosine similarity, JSON parsing) with local Pyodide execution.
- Can recruiters see my scores?
- Yes on your public Ganloss talent profile, with the project you link after passing.
AI jobs you may like
Discord ML engineer jobs for content moderation and abuse detection — NLP and multimodal classifiers in San Francisco.
Remote Discord LLM engineer for community copilots and summarization — product GenAI with strong safety bars.
Remote US Groq ML systems role — runtime, scheduling, and developer APIs for high-throughput LLM inference.
Groq LLM inference engineer jobs — ultra-low-latency serving on LPUs, compiler tooling, and API performance in Mountain View.
ServiceNow MLOps engineer for model CI/CD and GPU serving — Bellevue / Seattle hybrid enterprise AI platform.
Sources: US AI/tech market data (2026), Ganloss job listings, public training catalogs.