Research Scientist (AI Agent Economies) | naptha.ai
About this role
We are seeking an exceptional Agent Economics Researcher to study and design incentive structures and economic systems for large-scale AI agent networks. This is a rare opportunity to shape the future of AI agent infrastructure at a massively ambitious scale, backed by industry veterans and technical leaders through NVIDIA Inception, Google for Startups, and Microsoft for Startups.
We're building the foundational infrastructure for the next wave of AI companies, enabling frontier AI developers (many leaving labs like OpenAI, Anthropic, and DeepMind) to build products powered by enormous networks of highly capable next-generation AI agents. As our Agent Economics Researcher, you'll develop the theoretical and practical frameworks for how agents cooperate, compete, and create value within complex networks.
Core Responsibilities
Design and study economic mechanisms for agent networks
Research incentive structures for agent collaboration
Develop frameworks for resource allocation and optimization
Study economic behavior patterns in agent systems
Create models for agent value creation and exchange
Research market dynamics in agent networks
Design experiments to validate economic theories
Research Areas
Mechanism design for agent systems
Game theory in multi-agent networks
Resource allocation optimization
Market design for agent economies
Incentive alignment in agent networks
Economic efficiency in distributed systems
Value creation and capture in agent networks
You're a good fit if you have:
PhD or equivalent experience in Economics, Computer Science, or related field
Strong background in mechanism design and game theory
Experience with multi-agent systems or markets
Understanding of distributed systems economics
Strong mathematical and analytical skills
Interest in both theoretical and applied research
Ability to translate economic theory into practical systems
Required Experience:
Research experience in economics or mechanism design
Strong mathematical and modeling skills
Programming ability for economic simulations
Track record of novel research contributions
Understanding of distributed systems
Experience with experimental design
About the hiring process:
Research presentation
Economic design challenge
Technical discussion
Team collaboration interview
Vision and strategy workshop
Compensation & Benefits:
Highly competitive salary and significant equity stake
Remote-first work environment
Full medical, dental, and vision coverage
Flexible PTO policy
Research conference budget
Publication support
Learning and development budget
Additional Notes:
Must be comfortable with ambiguity and rapid iteration typical of pre-seed startups
Strong bias for practical implementation of research ideas
Passion for advancing the field of multi-agent systems
Interest in open source contribution and community engagement
This is a unique opportunity to shape the economic foundations of future AI systems, designing the mechanisms and incentives that will govern how agents interact and create value at scale.