Principal AI Engineer - Entourage
Principal AI Engineer - Entourage

Principal AI Engineer - Entourage

London Full-Time 43200 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead the design and development of AI systems for collective learning among agents.
  • Company: Entourage, incubated by Moonsong Labs, is revolutionising AI with shared memory protocols.
  • Benefits: Enjoy a dynamic work environment with opportunities for innovation and growth.
  • Why this job: Be at the forefront of AI technology, shaping the future of collective intelligence.
  • Qualifications: Experience in AI architectures, with expertise in Generative AI and multi-agent systems required.
  • Other info: This role offers potential for leadership and collaboration with cutting-edge technologies.

The predicted salary is between 43200 - 72000 £ per year.

About 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.

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

– Tanssi – Decentralised AppChain infrastructure secured via Restaking

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 Foundation

At Moonsong Labs, we pride ourselves on being an innovative employer that fosters a collaborative and inclusive work culture, particularly for our Principal AI Engineer role within Entourage. Our commitment to employee growth is evident through opportunities to lead cutting-edge projects in AI and Web3, while our dynamic environment encourages creativity and the sharing of ideas. Located at the forefront of technological advancement, we offer unique advantages such as access to pioneering resources and a supportive team dedicated to shaping the future of collective intelligence.
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Contact Detail:

Web3 Foundation 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 knowledge will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.

✨Tip Number 2

Showcase your experience with AI architectures and infrastructure by preparing specific examples of past projects. Be ready to discuss how you overcame challenges and delivered complex software platforms, as this will demonstrate your capability to thrive in a fast-paced environment.

✨Tip Number 3

Network with professionals in the AI and Web3 space. Attend relevant meetups or webinars to connect with others who share your interests, as these connections can provide valuable insights and potentially lead to referrals.

✨Tip Number 4

Prepare to discuss your strategic thinking regarding platform adoption and developer ecosystems. Understanding how to foster collaboration and innovation within a team will be crucial for a leadership role in this position.

We think you need these skills to ace Principal AI Engineer - Entourage

AI Architecture Design
Distributed Systems Engineering
Generative AI Expertise
Multi-Agent Systems Knowledge
Reinforcement Learning Implementation
End-to-End MLOps
Deep Learning Proficiency
Knowledge of Federated Learning
AI Safety Awareness
Secure Agent Execution Techniques
Familiarity with Multi-Agent Frameworks (e.g., LangGraph, LangChain)
Understanding of Communication Standards (e.g., MCP, A2A)
Consensus Mechanisms Knowledge
Leadership and Team Supervision Skills
Strategic Thinking in Platform Adoption
Blockchain and Web3 Familiarity
Tokenomics Understanding
Postgraduate Degree in STEM

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 at Entourage. Familiarise yourself with their focus on collective intelligence and the technologies mentioned in the job description.

Tailor Your CV: Customise your CV to highlight relevant experience in AI architectures, multi-agent systems, and any specific technologies mentioned, such as Generative AI or reinforcement learning. Use keywords from the job description to ensure your application stands out.

Craft a Compelling Cover Letter: Write a cover letter that not only showcases your technical skills but also demonstrates your passion for AI and collective learning. Mention how your previous experiences align with the goals of Entourage and Moonsong Labs.

Showcase Your Projects: If you have worked on relevant projects, especially those involving AI systems or distributed infrastructure, be sure to include them in your application. Provide links to your work or GitHub repositories to give the hiring team a clear view of your capabilities.

How to prepare for a job interview at Web3 Foundation

✨Showcase Your AI Expertise

Make sure to highlight your previous experience in 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 Leadership Skills

Since this role is expected to grow into a leadership position, be ready to share examples of how you've led teams or supervised other engineers. Discuss your approach to mentoring and fostering collaboration among team members.

✨Stay Updated on Industry Trends

Familiarise yourself with the latest advancements in multi-agent systems, collective learning, and AI safety. Showing that you are aware of state-of-the-art developments will demonstrate your passion and commitment to the field.

✨Prepare for Technical Questions

Expect to face technical questions related to generative AI, reinforcement learning, and distributed systems. Brush up on relevant frameworks and communication standards, as well as your understanding of tokenomics and Web3 concepts.

Principal AI Engineer - Entourage
Web3 Foundation
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  • Principal AI Engineer - Entourage

    London
    Full-Time
    43200 - 72000 £ / year (est.)

    Application deadline: 2027-08-16

  • W

    Web3 Foundation

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