Moonsong Labs is hiring a

Web3 Principal AI Engineer - Entourage

We're building the infrastructure layer that will power the next generation of AI agents: collective intelligence. Entourage is a shared memory protocol that lets AI agents learn from each other's discoveries, building collective intelligence that gets smarter with every interaction. We capture successful workflows, assimilate patterns, and enable instant retrieval so that agents never have to solve the same problem repeatedly. Our approach goes beyond existing agent frameworks, creating the connective tissue for the emerging agent economy where AI systems discover capabilities, learn collectively, and collaborate to create value.

What you'll do:

• Lead the end-to-end design and development of core AI systems that enable collective learning and shared memory among autonomous agents.
• Architect and implement scalable distributed infrastructure for capturing, validating, and surfacing agent experiences across complex networks at scale..
• Drive innovation in protocol-level mechanisms for memory curation, knowledge consolidation, and token-incentivized participation across mutually distrusting agents.
• Build frameworks and tooling that allow agents to transform episodic episodic experiences and action trajectories into reusable, network-wide intelligence.
• Collaborate closely with the CTO to operationalize cutting-edge work in reinforcement learning, LLMs, and multi-agent coordination into production-grade systems.
• Define and uphold technical standards for code quality, security, reliability and scalability across the AI and protocol layers.

What you'll bring:

• Previous experience in AI architectures and infrastructure, with a proven track record of delivering complex software platforms and AI-native products.
• Proven track record of shipping production systems or prototypes at high velocity, ideally in startup or research contexts where speed and adaptability are paramount.
• Deep expertise in Generative AI, multi-agent systems, LLMs, end-to-end MLOps, and AI infrastructure. Exposure to Deep Learning, Reinforcement Learning, federated learning, AI evaluation or ML fundamentals is highly beneficial.
• Active interest and awareness of SOTA in multi-agent systems, collective learning, AI safety, secure agent execution, emerging AI agent architectures, and tool integration.
• Familiarity with one or more multi-agent frameworks (such as LangGraph, LangChain, CrewAI, AutoGen, and Pydantic AI), communication standards (such as MCP, A2A, Story’s Agent TCP/IP, Near’s AITP), distributed systems, distributed AI architectures, and consensus mechanisms.
• Ability to lead and supervise other engineers and AI scientists; this role is expected to grow into a leadership position and is not limited to individual contribution.
• Strategic thinking about platform adoption, scalable developer ecosystems, and familiarity with the Blockchain, Web3, and tokenomics (beneficial but not required).
• Postgraduate degree in a STEM field (Master’s required; PhD strongly preferred).

Equal Opportunity is the law, and at Moonsong Labs, we are ardently committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. If you have a specific need that requires accommodation, please let us know.