M&A Attorney

RemoteJobsOne; Toronto; Remote; CAD 124,000 - 179,000; Part time

Job summary

RemoteJobsOne is seeking an experienced M&A Attorney for a part-time, fully remote contract role open to candidates in Canada. You will draft, review, negotiate, and redline M&A agreements, and contribute to AI-driven contract evaluation training.

You will assess AI outputs, develop evaluation frameworks, and collaborate with product and research teams in a fast-paced tech environment.

Qualifications

• J.D. from ABA-accredited law school required.
• Active bar admission in at least one U.S. jurisdiction required.
• Minimum of 2 years in the M&A department of a corporate law firm required.
• Familiarity with standard M&A agreements including APAs and SPAs.
• Strong written and verbal communication with meticulous attention to detail.
• Ability to translate legal expertise into actionable feedback for AI systems.

Responsibilities

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

Skills

Contract drafting

Negotiation

Legal analysis

Cross-functional teamwork

Written & verbal communication

AI in law

Education

J.D. from ABA-accredited law school

Bar admission in US jurisdiction

Tools

APAs

SPAs

Job description

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

Pay: $90–$130/hr

Role Title: M&A Attorney

Role Type: Contractor

Location: Remote

We are seeking seasoned M&A attorneys 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. J.D. from an ABA-accredited law school.
2. Active bar admission in at least one U.S. jurisdiction.
3. Minimum of 2 years in the M&A department of a corporate law firm.
4. Familiarity with standard M&A agreements, including APAs and SPAs.
5. Exceptional written and verbal communication skills with meticulous attention to detail.
6. Strong analytical capabilities and ability to translate legal expertise into actionable feedback for AI systems.
7. Demonstrated commitment to innovation at the intersection of law and technology.
8. Experience working with cross-disciplinary teams in fast-paced environments.

Preferred Qualifications:

1. Prior exposure to AI, legal tech, or training initiatives.
2. Experience working with 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.