Left OpenAI in early 2026 after about 14 months. Writing this because every thread I found before joining was either a puff piece or completely unhinged negativity. Reality is more textured.
The short version: it depends almost entirely on which team you land on, what phase the product is in, and frankly how much personal runway you have before burnout.
The hours are real. Not startup-theater real where everyone posts 9pm Slack messages for optics. Actually real. The reasoning models team during a major launch was pulling what looked like 60-70 hour weeks consistently for months. Safety Evals had stretches of relative calm, then brutal crunch before model releases. If you're used to big-company engineering where the sprints are mostly 40 hours with the occasional fire, adjust expectations significantly.
The culture is intense and mission-driven in a way that can feel either energizing or suffocating depending on your personality. People genuinely believe the work matters. That belief is both the best and worst thing about the place. Best, because it creates real focus and smart people willing to dig in. Worst, because it can make you feel guilty for taking PTO or even logging off at 7pm. There's no explicit "you must work all hours" policy. The implicit norm is louder than any policy.
What it's actually like day to day. Lots of smart people, fast-moving environment, context switching is high. Org structure is flat in theory, less flat in practice. If you're someone who needs clear direction and stable priorities, the ambiguity will wear on you. If you thrive in an environment where the roadmap shifts based on new model capabilities, you might love it.
Comp. Competitive at the level I was hired in at (equivalent L5-ish SWE). Base was solid, equity was in the "this matters a lot" tier given the valuation trajectory. Tender offers have been a real thing but don't count on them.
Verdict on WLB. Not good by big-tech standards. Better than a true early-stage startup, maybe. If WLB is genuinely a top-three priority for you, go to Google or a well-run mid-stage company. If you want to be inside the most consequential AI lab in the world during the most consequential stretch in AI history, and you can absorb the pace, it's a legitimately rare opportunity. Both things are true at the same time.
7 replies
sec_sasha
I'd push back a little on the "most consequential AI lab" framing. That's the thing they tell you in the offer call. Whether it's actually true versus Anthropic, DeepMind, Google DeepMind now, whatever Meta is doing with Llama, is genuinely debatable. I think people should interrogate that assumption before signing, not just accept the narrative.
ae_andre
Fair. I don't disagree that the claim is contestable. My point wasn't that it's objectively true, it's that the people there believe it, and that belief shapes the culture for better and worse. You can decide for yourself whether the reality lives up to the belief.
staff_steph
The team dependency thing is real and undersold. I have a friend who joined the infrastructure side and describes a pretty normal, sane work environment. Another friend on a research team during a model push described the same thing you did, 60+ hours, ambient guilt about leaving. Same company, wildly different experience. Ask specifically about the team's launch cadence and on-call expectations in the final round. Recruiters give you the company average, which is meaningless.
director_dee
As someone who has hired people who came out of OpenAI: they tend to be sharp but occasionally have trouble recalibrating when they land somewhere with a slower pace. Some of them flourish. A few seemed genuinely burned out and needed six months to decompress before they were fully present. Not a criticism, just context if you're on the other side of this decision.
visa_vik
One thing nobody talks about: for those of us on H1B, the "is this sustainable" question is higher stakes. If you burn out and leave at the 11-month mark you're back on the 60-day clock. I ended up declining an OpenAI offer partly because of this. The comp was excellent but I needed a role I could count on staying in for 2+ years without destroying my mental health. Wanted to leave this here in case anyone else is doing that calculation.
newgrad_neil
This is something I never see mentioned. Thank you. I'm on OPT and the timeline pressure makes high-churn environments genuinely more risky for me than for a domestic candidate. Going to factor this into my ranking.
sdr_sky
The equity piece is worth thinking through carefully. The headline numbers sound great but the structure matters. What's the vesting schedule, are there cliffs, is there a secondary market for those shares before an IPO that may or may not happen, what's the strike price vs current 409A, how do you model the tax hit on an NSO grant. Most people sign without modeling any of this. If someone here is evaluating an OpenAI offer, please get a tax advisor involved. The comp can look very different once you actually run the numbers.