Join to apply for the Research Scientist (AI Agent Behavior) role at Naptha AI Join to apply for the Research Scientist (AI Agent Behavior) role at Naptha AI Research 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-generation 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 generation of agent systems.

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