Interview questions
Google AI engineer interview questions (2026)
6 real interview questions reported by engineers who interviewed at Google, spanning Software Engineering, Data Engineering. Every question is scored against a golden answer on the things Google actually grades — architecture, token efficiency, security and correctness — not just whether your code runs.
Google Software Engineering questions
- Trim conversation context to a token budget
Implement a top-level `solve(payload)` that trims a chat history to fit a token budget, always keeping the system message and the most recent turns. ## The solve contract `payloa
- Stream Aggregator Batches LLM Tokens Into Complete Sentences
Implement a top-level `solve(payload)` that batches streaming tokens into complete sentences. ## The solve contract `payload` is a dict: - `tokens` (list of str): fed in order; c
- AI Agent Loop Termination Bug Causes Excessive API Calls
Your AI agent is supposed to look up a user's order status and respond. In production it's making hundreds of API calls and timing out. The loop termination logic has a bug. Find i
- RAG Evaluation Pipeline Failing to Filter Low Quality Responses
Your evaluation pipeline is supposed to catch low-quality RAG responses before they reach users. In production, bad responses are scoring highly and getting through to users. Multi
- RAG Chatbot Fails to Answer Despite Successfully Retrieving Relevant Documents
A junior engineer built a RAG chatbot for internal documentation. Users report it constantly says "I don't have enough information to answer" even when the answer is clearly in the
Google Data Engineering questions
- Schema evolution resilience: versioning, compatibility layers, registry patterns
You receive event data in proto3 from 30+ upstream services. Schema changes happen weekly. How do you build a pipeline that survives schema evolution without breaking downstream co
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