Description review

Builder/Architect/Engineer Expert Consultant (Part-Time Contractor)

Brain Co. · USA · back to the listing

HR standards

51/100

needs work

Title ↔ description

65/100

needs work

Reads as

Unclear

no confident match

What the listing never says

  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
  • No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

Our Mission

Rebuild how the world works, to make institutions work better for the people they serve.

About Brain Co.

Brain Co. builds AI-native operating systems for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model.

Why Now

Brain Co. is entering its next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia, and a growing footprint across government, insurance, health, and financial services.

Joining now means shaping both the company and a new category of applied AI. Every project here ships to production and is expected to create measurable customer value and impact.

You'll work alongside exceptional peers on some of the hardest problems in applied AI. It’s the kind of work you'll still be proud of in ten years from now.

About the Role

Brain Co. is building the world's first AI-native permitting, and we need people who've actually

done the work to help us get it right. You would play a role in helping shape AI Permitting in the US.

We're looking for 1) homebuilders and developers - production builders, custom builders, small regionals, and 2) architects, and 3) engineers to join us as part-time advisors. You'll work directly with our product and GTM teams, telling us where our AI falls short, what would actually change how you operate, and what it would take for a tool like this to earn a place in your workflow.

We are looking for someone for a minimum of 2 hours per week for 3-4 months. Opportunity to extend as needed.

What you'll do


Walk us through how you submit - Tell us what is included, what you’ve learned to front-load, where submissions get tripped up


Use the product on a project - Run a real permit package through our software alongside normal process


Tell us where we are wrong - Review AI output on real permit submissions and flag errors, gaps, or misapplied code


Jurisdiction knowledge - Help us understand how review actually works across different jurisdictions and permit types


Help us learn what a good submissions looks like - Review sample packages and tell us what would sail through, come back with comments, or get rejected

Who we're looking for


Someone who has personally submitted permits, not managed the process from a distance, but actually prepared packages, responded to comments, and tracked submissions through approval


Active or former plans examiner, permit engineer, architect of record, or homebuilder, anyone whose name is on the drawings or whose desk the rejection letter lands on


Deep knowledge of how permitting actually works in Florida, Texas, or California, the codes, the departments, the local amendments, and the unwritten rules


Enough history with a jurisdiction to tell us what reliably gets approved, what comes back with comments, and what gets rejected outright


Opinions about what's broken and no hesitation sharing them - "this is wrong because..." is exactly what we need


Open to sharing examples on applications (passed and failed)


No technical background required - your job is to tell us if the AI gets it right, not to explain how it works

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 8 points (from 59 before penalties). Reviewed 24 Sep 2026.