At a Glance
- Tasks: Lead the design and development of AI systems for collective learning among agents.
- Company: Moonsong Labs is a pioneering Web3 and AI venture studio transforming industries.
- Benefits: Enjoy flexible work options, innovative projects, and a collaborative culture.
- Why this job: Be at the forefront of AI innovation and contribute to a more equitable digital landscape.
- Qualifications: Experience in AI infrastructure, with a strong background in Generative AI and multi-agent systems.
- Other info: This role offers growth into leadership and the chance to shape future technologies.
The predicted salary is between 72000 - 108000 £ per year.
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.
About Moonsong Labs:
Entourage has been incubated by Moonsong Labs, a cutting-edge Web3 and AI venture studio driving next-wave developer and end-user adoption. Moonsong Labs creates software infrastructure and protocols at the intersection of Web3 and AI, disrupting traditional industries, empowering individuals, and fostering a more equitable digital landscape.
Recent ventures include:
– Kluster.ai – Anti-hallucination platform for Machine Learning models
– Moonbeam – EVM-compatible L1 blockchain optimised for cross-chain use cases
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).
Ready to Shape the Future? Join Us Today!
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.
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Principal AI Engineer Entourage employer: web3-resources
Contact Detail:
web3-resources Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal AI Engineer Entourage
✨Tip Number 1
Familiarise yourself with the latest advancements in multi-agent systems and collective learning. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the AI and Web3 space. Attend relevant meetups, webinars, or conferences to connect with like-minded individuals and potentially get referrals that could boost your application.
✨Tip Number 3
Showcase your leadership skills by discussing any past experiences where you led a team or project. Highlight how you drove innovation and collaboration, as this role is expected to grow into a leadership position.
✨Tip Number 4
Stay updated on the latest tools and frameworks related to AI infrastructure and multi-agent systems. Being knowledgeable about platforms like LangChain or CrewAI can set you apart from other candidates.
We think you need these skills to ace Principal AI Engineer Entourage
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Principal AI Engineer position. Familiarise yourself with the concepts of collective intelligence, multi-agent systems, and the technologies mentioned in the job description.
Tailor Your CV: Customise your CV to highlight relevant experience in AI architectures, infrastructure, and any specific projects that align with the role. Emphasise your track record of delivering complex software platforms and your expertise in Generative AI and multi-agent systems.
Craft a Compelling Cover Letter: Write a cover letter that not only showcases your technical skills but also your passion for AI and Web3 technologies. Mention how your background aligns with Moonsong Labs' mission and how you can contribute to their innovative projects.
Showcase Relevant Projects: If you have worked on projects related to reinforcement learning, distributed systems, or any of the frameworks mentioned, be sure to include these in your application. Provide links to your work or GitHub repositories to demonstrate your capabilities.
How to prepare for a job interview at web3-resources
✨Showcase Your AI Expertise
Make sure to highlight your previous experience with AI architectures and infrastructure. Be prepared to discuss specific projects where you delivered complex software platforms or AI-native products, especially in fast-paced environments.
✨Demonstrate Knowledge of Multi-Agent Systems
Familiarise yourself with the latest advancements in multi-agent systems and collective learning. During the interview, share your insights on how these concepts can be applied to enhance the functionality of the Entourage protocol.
✨Discuss Your Leadership Experience
Since this role is expected to grow into a leadership position, be ready to talk about your experience in leading teams. Share examples of how you've supervised engineers or AI scientists and fostered collaboration in past projects.
✨Prepare for Technical Questions
Expect to face technical questions related to distributed systems, reinforcement learning, and AI safety. Brush up on relevant frameworks and communication standards, and be ready to explain how they relate to the role you're applying for.