Forward-deployed work has always depended on people manually translating a customer's operation into software. World AI OS changes that: Brain holds the workflow context, Studio and Factory turn a diagnosed opportunity into a governed system, and Control keeps evidence and approval behind every decision.
That means engineers spend less time re-deriving what a client already knows about their own business, and more time building the system that changes it.
You think AI-native workflows will reshape how entire functions operate, and you want to be the one building that shift — not integrating AI into the old way of working.
Ideas become prototypes, prototypes become production systems. You'd rather test something with the client this week than debate requirements for another month.
You question assumptions and go find the answer instead of guessing. "I don't know yet, but I'll find out" is a normal thing to say here.
Feedback here is fast and specific, aimed at making the work better — not at making anyone feel good about it.
The technology moves fast enough that any given approach has a short shelf life. Stay attached to the outcome the client needs, not to the way you first built it.
Engineers work in small pods against a specific engagement — usually a Discovery Sprint that's moved into build, or an operation already live on World AI OS. You'll spend stretches embedded with the client's own team, not rotating between unrelated tickets.
The team is remote-first and distributed, with in-person time built around client engagements and quarterly team gatherings rather than a fixed office. What's constant is the platform: Brain, Studio, Factory, and Control — the four layers of World AI OS that every pod builds against and contributes back to.
We make room for exceptional early-career candidates, but most roles are filled by experienced hires.
We're not able to give individual feedback on applications, but every submission to the talent pool is reviewed.
We evaluate this case by case. If sponsorship applies to you, raise it early so we can plan around it.
Remote-first by default. Most roles include stretches on-site with a client or with the team, depending on the engagement.
We're not running fixed job postings right now — every role below feeds the same talent pool, reviewed as engagements open up.
Build Brain, Studio, Factory, and Control themselves — the workflow intelligence, modelling, and governance infrastructure every engagement runs on.
Design, evaluate, and operate the models and agents that run inside a client's live workflow — accountable for how they perform in production, not in a demo.
Embed directly inside a client's engagement — translate their actual workflow into a system built on World AI OS, and stay accountable until it's running.