Corporate Counsel

RemoteJobsOne

Zürich

Remote

CHF 115.000 - 149.000

Teilzeit

Vor 6 Tagen
Sei unter den ersten Bewerbenden
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Zusammenfassung

RemoteJobsOne is seeking a seasoned in-house Corporate Counsel for a part-time, fully remote role open to Switzerland-based candidates. You will review and redline technology contracts, provide feedback to AI training systems, and contribute to risk assessment in real-world legal work.

The ideal candidate has at least 3 years' experience in tech transactions, excels in clear written and verbal communication, and can collaborate with product and research teams to refine guidelines for AI-driven

Qualifikationen

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

Aufgaben

  • Perform simulated contract negotiations and redlining exercises.
  • Review AI responses to contract scenarios and provide feedback.
  • Create evaluation frameworks and grading criteria for AI contract tasks.
  • Collaborate with product and research teams to refine guidelines for AI-driven contract review.

Kenntnisse

In-house experience
Technology transactions
Contract negotiations
MSAs/NDAs/DPAs
AI/Legal tech familiarity

Jobbeschreibung

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


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.

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