Brain Co. · San Francisco
OtherProductRemoteContractposted 4w ago
Rebuild how the world works, to make institutions work better for the people they serve.
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.
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.
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.
• 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.
• 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.
Candidates may be especially well suited if they have experience in one or more of the following areas:
• In-house commercial legal work
• Private equity, investment, M&A, funds, credit, real assets, or other transactional practices
• Cross-border transactions or international commercial agreements
• Working with investment organizations, financial institutions, sovereign entities, or complex multinational businesses
• Managing external counsel or reviewing external counsel advice and issue lists
• Developing contract playbooks, clause libraries, fallback positions, or approval frameworks
• Legal operations, contract lifecycle management, matter management, or knowledge management
• Post-signing obligations, closing checklists, amendments, consents, governance, or asset-management legal work
Deep experience in every area is not required. We are primarily looking for strong commercial legal judgment, the ability to explain that judgment clearly, and interest in helping shape a new AI product.
• 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
• Enjoy explaining how experienced lawyers reach decisions, including the judgment calls that are rarely captured in formal policies
• Can translate complex legal reasoning into clear, structured guidance
• Are comfortable challenging assumptions and saying, "This is not how a lawyer would approach the problem"
• Can distinguish between legally correct analysis and analysis that is actually useful in a time-sensitive commercial workflow
• Care about provenance and can point to the clause, document, playbook position, precedent, or factual context supporting a conclusion
• Are comfortable working in shared documents, asynchronous communication tools, and structured annotation or review interfaces
• Are interested in shaping how AI supports lawyers without replacing lawyer-controlled judgment
• This engagement involves exposure to sensitive commercial agreements and internal product information. A signed Non-Disclosure Agreement (NDA) will be required before work begins.
• Part-time contract engagement, U.S.-based candidates only
• Approximately 5–10 hours per week
• Initial engagement of 3–4 months, with the opportunity to extend
• Flexible scheduling designed to work alongside an existing legal role or practice
• Remote-friendly, with collaboration through shared documents, asynchronous communication, and recurring working sessions with Brain Co.'s product and engineering teams
• A signed NDA is required prior to starting work
• Competitive hourly compensation commensurate with experience and depth of expertise