Infrastructure Engineer deep-dive: ‘Design an in-memory cache system with CRUD operations, key-value store, optional data expiry, and high concurrency support.’ Had to handle threading, memory management, and eviction policies. System design: ‘How would you architect GPU resource allocation across 1000s of training jobs with dynamic priority?’ Also: ‘Implement a monitoring system that detects anomalous GPU usage patterns in real-time.’ Infrastructure at OpenAI means handling unprecedented compute scale while maintaining reliability.
Applied Research Scientist questions: ‘Discuss the Attention is All You Need paper and explain how you’d modify the attention mechanism for longer sequences.’ ‘How would you design an experiment to measure hallucination rates across different model sizes?’ Coding: ‘Implement multi-head attention from scratch and explain each component.’ Behavioral: ‘How do you balance research exploration vs product timelines when your research could impact millions of users?’ They expect deep paper knowledge and ability to translate research to production.
Partnership/Business Development interview: ‘OpenAI wants to partner with a major enterprise software company. Design the partnership strategy, technical integration plan, and go-to-market approach.’ ‘How would you structure a deal where the partner gets access to GPT-5 capabilities 6 months before public release?’ ‘Navigate a scenario where a key enterprise partner threatens to switch to a competitor due to API reliability issues.’ Partnership roles require understanding both technical capabilities and business strategy.
Operations/Business Strategy role: ‘Design the operational framework for scaling OpenAI from 3,500 to 10,000 employees while maintaining culture and safety standards.’ ‘How would you structure the decision-making process for model releases that could impact global markets?’ ‘Create a framework for prioritizing R&D investments across 15 different AI research directions.’ Operations at OpenAI isn’t traditional ops - it’s about scaling an organization building AGI while maintaining responsibility.
Legal/Policy role insights: ‘Draft a policy framework for AI agent deployment in regulated industries like healthcare and finance.’ ‘How would you structure international compliance when different countries have conflicting AI regulations?’ ‘Create a legal review process for research papers that might contain dual-use information.’ ‘Design a framework for handling government requests for model capabilities that could be misused.’ Legal at OpenAI means navigating uncharted territory where precedent doesn’t exist.
Cross-role interview patterns I’ve observed: 1) Every role now requires AI safety awareness - from finance to legal to partnerships. 2) Questions assume rapid change - ‘How does this strategy adapt when model capabilities double every 18 months?’ 3) Scale thinking is mandatory - all roles consider billion-user impact. 4) Ethics integration - not separate questions, but woven into technical and business scenarios. 5) Unprecedented challenges - roles involve problems that didn’t exist 2 years ago. The common thread: they want people who can navigate uncertainty while maintaining OpenAI’s safety-first culture.