Job DescriptionJob DescriptionResearch Scientist (AI Agent Behavior) | naptha.ai
About this role
We are seeking an exceptional Agent Behavior Scientist to study and optimize how AI agents interact, collaborate, and evolve within large-scale 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- AI agents. As our Agent Behavior Scientist, you'll develop novel approaches to understanding and optimizing agent behavior patterns and interaction dynamics.
Core Responsibilities
Study and analyze agent behavior patterns in complex networks
Design experiments to understand agent interaction dynamics
Develop frameworks for measuring agent effectiveness
Create models of agent behavior and collaboration
Research optimal patterns for agent coordination
Identify and address behavioral failure modes
Shape the evolution of agent interaction patterns
Research Areas
Agent interaction patterns and dynamics
Emergent behavior in agent networks
Collaborative intelligence optimization
Agent communication effectiveness
Behavioral failure modes and solutions
Agent adaptation and learning patterns
Social dynamics in agent networks
You're a good fit if you have:
PhD or equivalent experience in AI, Complex Systems, Cognitive Science, or related field
Deep understanding of multi-agent systems and behavior
Experience studying emergent behavior in complex systems
Strong analytical and experimental design skills
Track record of novel research in agent systems
Ability to translate behavioral insights into practical improvements
Interest in both theoretical and applied research
Required Experience:
Proven research experience in agent systems or related fields
Strong programming and data analysis skills
Experience with experimental design and analysis
Track record of impactful research publications
Understanding of AI/ML fundamentals
Experience with behavioral analysis frameworks
About the hiring process:
Research presentation and discussion
Experimental design challenge
Behavioral analysis deep dive
Team collaboration interview
Research vision 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 study and shape how AI agents behave and interact at scale, helping define the patterns that will govern the next of agent systems.
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