For engineers moving into AI
Free, sourced guides for AI engineer interviews at OpenAI, Anthropic, Google, Meta, xAI and frontier labs — RAG, agents, evals, inference, compensation and interview loops.
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What public data reveals about OpenAI TPM compensation in 2026, from PayScale industry benchmarks to Comparably estimates and live job board analysis.
Read · 9 min →Mistral AI SDE interview breakdown: LeetCode patterns, priority coding topics, round difficulty vs FAANG, system design role, prep checklist & mistakes to avoid.
Read · 7 min →What public sources show about OpenAI and Google work culture, work-life balance, interview process and pay bands, plus a preparation checklist for candidates.
Read · 4 min →Real PM interview questions at Together AI with structured answers, evaluation criteria, and a preparation checklist for AI infra product roles.
Read · 21 min →Apple AI engineers earn an average of $250,000, with top performers making over $400,000 and role-based ranges from $150,000 to $420,000.
Read · 4 min →Topics
Chunking, hybrid search and retrieval evals for production RAG.
Explore →Agent architectures, tool use and orchestration that survive real traffic.
Explore →LLM-as-judge, offline and online evals, and how interviewers test them.
Explore →Interview loops, levels and compensation at AI labs and Big Tech.
Explore →The playbook
The interview loop that didn't exist two years ago, in one book: what AI engineer interviewers evaluate, the skill stack they probe, and LLM system design end to end.
New and updated guides on LLM systems, AI interviews and AI engineering careers.
The AI engineer interview, mapped round by round: the LLM fundamentals, RAG and system design, coding and behavioral questions that public question banks cover, each with a reusable answer framework, plus practice drills and a four-week prep plan.
10 min read
The public record on pace and culture at Cursor maker Anysphere, with sourced ratings and a labeled checklist for judging WLB before you join a fast-moving AI startup.
6 min read