Principal AI Engineer - Entourage

Principal AI Engineer - Entourage

Posted 2 weeks ago by Entourage

Negotiable
Undetermined
Undetermined
London, England, United Kingdom

Summary: The Principal AI Engineer at Moonsong Labs will lead the design and development of advanced AI systems that facilitate collective learning among autonomous agents. This role involves architecting scalable infrastructure, driving innovation in memory curation, and collaborating with the CTO to implement cutting-edge AI technologies. The position requires a strong background in AI architectures and a proven ability to deliver complex software solutions rapidly. The ideal candidate will also have leadership potential and a strategic mindset regarding platform adoption and developer ecosystems.

Key Responsibilities:

  • Lead the end-to-end design and development of core AI systems.
  • Architect and implement scalable distributed infrastructure for agent experiences.
  • Drive innovation in protocol-level mechanisms for memory curation and knowledge consolidation.
  • Build frameworks and tooling for transforming episodic experiences into network-wide intelligence.
  • Collaborate with the CTO to operationalize work in reinforcement learning and multi-agent coordination.
  • Define and uphold technical standards for code quality, security, reliability, and scalability.
  • Mentor, lead, and supervise other engineers, with potential for growth into a leadership position.

Key Skills:

  • Experience in AI architectures and infrastructure.
  • Proven track record of delivering complex software platforms and AI-native products.
  • Deep expertise in Generative AI, multi-agent systems, and end-to-end MLOps.
  • Familiarity with multi-agent frameworks and communication standards.
  • Ability to mentor and lead engineering teams.
  • Postgraduate degree in a STEM field (Master's required; PhD preferred).

Salary (Rate): undetermined

City: London

Country: United Kingdom

Working Arrangements: undetermined

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Moonsong Labs London, United Kingdom Full Time Reference: 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 crypto token-incentivized participation across mutually distrusting agents. Build frameworks and tooling that allow agents to transform 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. 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 working with 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 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 mentor, lead, and supervise other engineers; 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). LNKD1_UKTJ