Engineer in Residence: General Counsel

United States·Mountain ViewContractmid

OtherEngineerGeneral Counsel

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In-house legal teams are drowning in contract volume, compliance obligations, and cross-functional requests but legal headcount doesn't scale with company growth.

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OtherEngineerGeneral Counsel

In-house legal teams are drowning in contract volume, compliance obligations, and cross-functional requests but legal headcount doesn't scale with company growth. This role is to build an AI-native general counsel product for SMBs: starting with contract review and clause extraction, and growing into the always-on legal operations layer that sits between operators and outside firms.

A contract ingestion and parsing pipeline that handles PDFs, Word documents, and email attachments across varying formats and clause structures.

A clause extraction and classification system that identifies key terms, obligations, risk provisions, and non-standard language with high precision.

A risk scoring engine that flags contracts or clauses that deviate from company-approved templates or contain unusual terms.

A workflow layer that routes flagged items to the right reviewer with context, reducing the time from contract receipt to approval.

Design the document processing pipeline for handling the full diversity of enterprise contract formats.

Build extraction models that identify and classify contract clauses with precision high enough for legal teams to trust.

Develop a risk assessment framework that compares incoming contracts against company playbooks and approved clause libraries.

Implement a review workflow that integrates with existing legal tools (CLMs, matter management systems, email).

Work with in-house legal design partners to validate accuracy and build trust in AI-assisted contract review.

Strong full-stack or backend engineering skills. You have built and shipped production systems that process complex documents.

Experience with document processing, NLP, or information extraction from unstructured text.

Hands-on experience building with LLMs, particularly for structured data extraction, classification, or reasoning tasks.

Ability to build systems where precision matters. Legal teams need to trust the output, so false positive management is critical.

Ability to work autonomously and make product and architecture decisions without waiting for direction.

Experience in legal tech, compliance tech, or regulated industry software.

Familiarity with contract lifecycle management (CLM) tools or legal workflow systems.

Background in document AI, OCR, or PDF processing pipelines.

Founder or founding engineer experience building for knowledge worker workflows.

A builder who sees legal operations as a high-value, underserved vertical for applied AI.

Someone who understands that the hardest part is not extraction but precision: legal teams will not use a tool that makes mistakes on important clauses.

This is a 12-week, full-time, on-site residency in Mountain View, California.

Not every residency becomes a company. The goal is to pressure-test the idea quickly and honestly with real users and customers.

You will be building an AI Fund idea, not bringing your own startup idea into the program.

The process typically includes a Builder Event or equivalent working conversation, then a 48-hour Builder Challenge, then panel review with AI Fund build leadership.

The compensation is intentionally modest during the residency because the upside, if the idea works, is a founder-level role.

$10,000/month for 12 weeks ($30,000 total). This is a contract role during the residency. If the build leads to a funded company, the next step is a founder-level role with meaningful equity upside.