Commercial/Transactional Lawyer

Brain Co.

1d•Remote

About The Position

Brain Co. is building an AI-powered legal work surface for a large global investment organization. The product is intended to help in-house lawyers manage legal work across matters, emails, documents, playbooks, prior transactions, external counsel outputs, and internal systems. We are looking for an experienced commercial or transactional lawyer to join us as a part-time domain expert. You will work directly with our product and engineering teams to help us understand how experienced lawyers review agreements, evaluate risk, use precedent, make negotiation decisions, and manage matters from intake through signing and post-close follow-up. Initially, the role will focus heavily on structured working sessions with the team. We will ask you to walk through legal workflows, answer domain questions, challenge product assumptions, and help us distinguish legally meaningful issues from details that do not materially affect a lawyer's decision. Over time, the role will also include reviewing AI-generated outputs, developing evaluation criteria, creating benchmark examples, and producing high-quality ground-truth data for model training and evaluation. We are looking for someone who can commit approximately 5–10 hours per week for an initial 3–4 months, with the opportunity to extend based on mutual interest and project needs. Scheduling can be flexible and designed to work alongside an existing role or legal practice.

Requirements

Must be based in the United States.
5+ years of legal experience preferred, with meaningful hands-on experience reviewing, drafting, and negotiating commercial or transactional agreements. Candidates with somewhat fewer years but especially relevant experience may also be considered.
Experience as an in-house lawyer, senior associate, legal consultant, or transactional counsel supporting complex organizations or sophisticated commercial clients.
Strong experience with commercial agreements such as NDAs, services agreements, procurement or vendor agreements, technology agreements, licensing agreements, transaction documents, or other negotiated contracts.
Ability to independently review an agreement, identify the issues that matter, evaluate practical risk, and explain the reasoning behind a recommended position.
Experience using playbooks, precedent, prior agreements, negotiation history, or organizational risk tolerance when advising on contract positions.
Strong written communication skills. You will be producing structured explanations and written evaluations, not only providing verbal advice.
Ability to explain legal concepts clearly to engineers, product managers, designers, and other non-lawyers.
Comfort working with incomplete information and clearly distinguishing between what can be concluded from the available documents, what requires additional factual context, what should be escalated to a lawyer or business stakeholder, and what should not be determined by an AI system.
A practical, opinionated perspective on what makes legal technology useful or unhelpful in real legal work.
Qualification or admission as a lawyer in a U.S. jurisdiction.

Nice To Haves

Experience with legal AI, contract review software, CLM systems, knowledge-management tools, or AI-assisted drafting products
Prior work with product, engineering, data science, or innovation teams
Experience creating legal training materials, review rubrics, model answers, or quality-control processes
Prior data annotation, evaluation, benchmarking, or expert-review work
Familiarity with tools such as iManage, DealCloud, Legora, Spellbook, Ironclad, or similar legal and transaction-management systems

Responsibilities

Help us understand real legal workflows — Walk the team through how legal requests arrive, how matters are organized, how documents are reviewed, how questions are escalated, and how decisions and rationale are preserved.
Answer nuanced legal and product questions — Provide practical guidance to product managers and engineers on commercial agreements, matter workflows, risk assessment, negotiation strategy, and legal operations.
Review product concepts and workflows — Evaluate whether proposed AI experiences reflect how lawyers actually work and identify missing steps, edge cases, or unrealistic assumptions.
Explain legal judgment — Help us understand not only what a clause says, but why a lawyer might accept it, reject it, propose a redline, seek additional context, or escalate it for approval.
Review AI-generated outputs — Assess summaries, issue identification, clause classifications, redline recommendations, obligation extraction, precedent retrieval, and other AI outputs for correctness, usefulness, and appropriate legal reasoning.
Develop evaluation rubrics and benchmarks — Help define what a high-quality output looks like and create representative examples that can be used to train, test, and improve our AI systems.
Generate high-quality ground-truth data — Review agreements and related materials, label legally relevant information, document the supporting evidence, and provide concise written reasoning for your conclusions.
Help us model institutional legal knowledge — Advise on how playbooks, prior positions, counterparty history, precedent, approvals, and negotiation rationale should inform future legal recommendations.
Provide direct, specific feedback — Tell us where the product is incorrect, incomplete, too confident, or unlikely to earn the trust of an experienced lawyer.
Occasionally support customer discovery — Join selected working sessions or customer conversations when domain expertise would help clarify requirements or validate a proposed workflow.