Corporate Counsel

RemoteJobsOne; Ciudad de México; A distancia; MXN 2.521.000 - 3.278.000; A tiempo parcial

Descripción de la vacante

RemoteJobsOne is seeking a seasoned Corporate Counsel for a fully remote, part-time contract role based in Mexico. The ideal candidate will draft, review, negotiate, and redline technology contracts while shaping AI-driven contract review processes for higher precision and risk control.

You will work with cross-functional teams to evaluate AI outputs, contribute to training data, and develop rigorous evaluation frameworks to ensure quality and compliance in a fast-paced, technology-forward

Formación

• Minimum of 3 years of in-house experience focused on technology transactions.
• Experience negotiating MSAs, NDAs, and DPAs.
• Excellent written and verbal communication skills with meticulous attention to detail.
• Ability to translate legal expertise into actionable feedback for AI systems.
• Experience collaborating with cross-disciplinary teams in fast-paced environments.

Responsabilidades

• Perform simulated contract negotiations and redlining exercises.
• Review AI responses to contract scenarios and provide expert feedback to improve model performance.
• Create evaluation frameworks and grading criteria to assess AI contract tasks.
• Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions.

Conocimientos

In-house tech transactions

Excellent written communication

Verbal communication

Analytical thinking

Cross-functional collaboration

Descripción del empleo

This is a fully remote position, open to candidates based in Mexico.

Pay: $100–$130/hr

Role Title: Corporate Counsel

Job Type: Contractor

Location: Remote

Job Summary:

We are seeking seasoned in-house Corporate Counsels for a part-time role at the forefront of legal AI. This opportunity is for elite lawyers who want to help shape how advanced AI is trained, evaluated, and applied in real-world legal work, especially those who have deep experience with drafting, reviewing, negotiating, and redlining within the tech field.

In this role, you will review, assess, and contribute to contract redlining workflows used to train and evaluate state-of-the‑art AI models. Your work will directly improve how these systems identify risk and interpret contract language to create tools with improved precision and legal judgment.

Key Responsibilities:

1. Perform simulated contract negotiations and redlining exercises.
2. Review and assess AI responses to contract scenarios, providing expert feedback to improve model performance and output precision.
3. Create objective evaluation frameworks and grading criteria to assess AI performance on contract tasks with rigor and consistency.
4. Collaborate with product and research teams to refine data, guidelines, and best practices for AI‑driven contract review solutions.

Required Skills and Qualifications:

1. Minimum of 3 years of in‑house experience focused on technology transactions, particularly negotiating MSAs, NDAs, and DPAs.
2. Exceptional written and verbal communication skills with meticulous attention to detail.
3. Strong analytical capabilities and ability to translate legal expertise into actionable feedback for AI systems.
4. Demonstrated commitment to innovation at the intersection of law and technology.
5. Experience working with cross‑disciplinary teams in fast‑paced environments.

Preferred Qualifications:

1. Prior exposure to AI, legal tech, or training initiatives.
2. Experience at a corporate law firm in either M&A or fund formation for private equity firms.

Why Join:

1. This is an opportunity to work at the intersection of law and technology.
2. You will help define how AI is developed for a new generation of legal practitioners.
3. You will apply your experience in a high‑impact research environment.

Compensation Structure:

Compensation is task‑based, meaning experts are paid per completed task that meets the project specifications. The average handling time (AHT) is approximately 3.5 hours per task, and the effective hourly rate will depend on the number of tasks completed and successfully signed off.