Cognitive Science

Nuvnext; Región Centro; Hybrid; MXN 200,000 - 320,000; Full time

Job summary

Nuvnext is hiring in Mexico to study how people review and sign agent proposals, focusing on ensuring signatures count. This role collaborates with researchers to examine overtrust, fatigue, and review errors in real-world tasks and to design better agent explanations.

You will bring findings into product design and governance, helping products operate with credible human-agent interactions in mind. A strong emphasis on clear writing and rigorous studies is required.

Qualifications

• Degree in cognitive science, psychology, or related field.
• Interest in systems that act, not only theory.
• Strong written communication.

Responsibilities

• Study how people review and sign what an agent proposes.
• Measure overtrust, fatigue and review errors.
• Propose how an agent should explain itself so the signature counts.
• Bring findings into design and governance.

Skills

Clear writing

User studies

Interest in systems that act

Education

Cognitive science/psychology degree (finished or near finished)

Tools

Python

R

Nuvnext platform

Job description

What is critical gets signed by a person. That only works if the person understands what they are signing and doesn't sign everything out of fatigue. In Labs you study how people work alongside an agent and how that relationship is designed.

The role

• Study how people review and sign what an agent proposes.
• Measure overtrust, fatigue and review errors.
• Propose how an agent should explain itself so the signature counts.
• Bring findings into design and governance.

Your first 90 days

• Day 30

  You learn the agents and how they are signed off today.

• Day 60

  You design and run a study with real users.

• Day 90

  A design or judgment change comes out of your study.

Stack and tools

User studies Python or R Nuvnext platform

Must have

• A cognitive science, psychology or related degree, finished or nearly finished.
• Interest in systems that act, not only in theory.
• You write clearly.

Nice to have

• Human factors.
• Human-computer interaction.
• Data analysis.

What working here is like

What you build goes into products that operate real organizations. You work directly with the founders, with no layers between your code and production, under the same rule we give the intelligence: a person signs what is critical.