1 to 25 of 36 Permanent Multi-Agent System Jobs in London

role sits at the intersection of systems architecture, agentic AI workflows, and customer-facing problem solving. You’ll design multi-agent systems, build reusable primitives, and convert complex financial workflows into scalable automated products. You’ll work directly with leading … deployment, and scale. What You’ll Do Take ambiguous workflow requests and turn them into scoped, architected, implemented, and deployed multi-agent systems Build reliable multi-step, multi-agent ...

role sits at the intersection of systems architecture, agentic AI workflows, and customer-facing problem solving. You’ll design multi-agent systems, build reusable primitives, and convert complex financial workflows into scalable automated products. You’ll work directly with leading … deployment, and scale. What You’ll Do Take ambiguous workflow requests and turn them into scoped, architected, implemented, and deployed multi-agent systems Build reliable multi-step, multi-agent ...

Lambda, Step Functions). Build CI/CD pipelines for ML models, agents, and GenAI applications. Deploy LLMs and orchestrate multi-agent systems (LangChain, LangGraph, or custom). Create and maintain data pipelines (Airflow, dbt, Step Functions). Implement monitoring, observability … . Experience with MLflow , CI/CD tools, and automated testing. Hands-on with LLM deployment and multi-agent systems . Proven experience building data pipelines and production ML workflows. Strong grounding in software engineering best practices and cost optimisation. Nice ...

risk in financial terms (£X exposure), map behaviours to regulatory requirements, and detect cascade failures before they propagate through multi-agent systems • Protocol Integration : Implement monitoring for agent communication protocols (Model Context Protocol, Agent2Agent, Agent … through first principles • You communicate technical concepts clearly to non-technical stakeholders Highly Valued (Differentiated Candidates) • Publications or research in multi-agent systems, reinforcement learning, AI safety, or agent architectures • Experience at AI labs (Anthropic, OpenAI, DeepMind ...

risk in financial terms (£X exposure), map behaviours to regulatory requirements, and detect cascade failures before they propagate through multi-agent systems • Protocol Integration : Implement monitoring for agent communication protocols (Model Context Protocol, Agent2Agent, Agent … through first principles • You communicate technical concepts clearly to non-technical stakeholders Highly Valued (Differentiated Candidates) • Publications or research in multi-agent systems, reinforcement learning, AI safety, or agent architectures • Experience at AI labs (Anthropic, OpenAI, DeepMind ...

Build & Own AI Systems Design and ship LLM applications using modern orchestration, prompt frameworks, and evaluation loops Build multi-agent systems (planning, tool use, safety constraints, monitoring) Implement retrieval and vector-based architectures (RAG, embeddings, semantic workflows) Apply ontology … applied data engineering Strong hands-on experience with LLMs, RAG, vector stores, and embeddings Experience building or orchestrating multi-agent systems Strong Python skills and ability to ship production-grade code Experience with at least one major AI cloud ecosystem ...

Build & Own AI Systems Design and ship LLM applications using modern orchestration, prompt frameworks, and evaluation loops Build multi-agent systems (planning, tool use, safety constraints, monitoring) Implement retrieval and vector-based architectures (RAG, embeddings, semantic workflows) Apply ontology … applied data engineering Strong hands-on experience with LLMs, RAG, vector stores, and embeddings Experience building or orchestrating multi-agent systems Strong Python skills and ability to ship production-grade code Experience with at least one major AI cloud ecosystem ...

Lead , owning the technical vision and AI architecture for the engagement Design and oversee GenAI and Agentic AI solutions , including multi-agent systems, orchestration, and evaluation frameworks Guide the use of LLMs, ML models, and scenario-modelling techniques to support pricing … Generative AI and Agentic AI Proven experience designing and delivering enterprise-scale AI architectures Strong hands-on experience with LLMs, multi-agent systems, and ML pipelines Cloud expertise across GCP and/or Azure (Vertex AI, Azure AI, ML platforms, APIs ...

Lead , owning the technical vision and AI architecture for the engagement Design and oversee GenAI and Agentic AI solutions , including multi-agent systems, orchestration, and evaluation frameworks Guide the use of LLMs, ML models, and scenario-modelling techniques to support pricing … Generative AI and Agentic AI Proven experience designing and delivering enterprise-scale AI architectures Strong hands-on experience with LLMs, multi-agent systems, and ML pipelines Cloud expertise across GCP and/or Azure (Vertex AI, Azure AI, ML platforms, APIs ...

existing enterprise stack. Conversant with end-to-end Generative and Agentic AI solutions for enterprise use cases. Design familiarity with multi-agent systems capable of reasoning, planning, and executing tasks autonomously. Evaluate and select appropriate models, frameworks, and orchestration tools. Ability ...

existing enterprise stack. Conversant with end-to-end Generative and Agentic AI solutions for enterprise use cases. Design familiarity with multi-agent systems capable of reasoning, planning, and executing tasks autonomously. Evaluate and select appropriate models, frameworks, and orchestration tools. Ability ...

Develop and maintain traditional machine learning models (Regression, Classification, Clustering, Time-Series) to solve structured data problems Agentic Workflows: Build multi-agent systems using frameworks like LangGraph, AutoGen, or similar to automate complex analysis tasks Evaluation & Observability: Implement rigorous evaluation frameworks ...

Develop and maintain traditional machine learning models (Regression, Classification, Clustering, Time-Series) to solve structured data problems Agentic Workflows: Build multi-agent systems using frameworks like LangGraph, AutoGen, or similar to automate complex analysis tasks Evaluation & Observability: Implement rigorous evaluation frameworks ...

/ML engineer with real deployments, excellent communication skills and a passion for teaching. Required experience: Previously built and deployed multi-agent systems end-to-end Strong hands-on expertise with LangGraph Experience with knowledge graphs, RAG and LLM tool orchestration ...

with strategic innovation. Key Responsibilities Design, build, and deploy AI agents using frameworks such as LangChain, CrewAI, or similar. Integrate multi-agent systems into existing software products and business workflows. Collaborate with stakeholders to identify automation opportunities and deliver agentic solutions. ...

with strategic innovation. Key Responsibilities Design, build, and deploy AI agents using frameworks such as LangChain, CrewAI, or similar. Integrate multi-agent systems into existing software products and business workflows. Collaborate with stakeholders to identify automation opportunities and deliver agentic solutions. ...

design and build production-grade AI systems across: LLM applications using modern orchestration patterns, prompt frameworks, and evaluation loops. Multi-agent architectures , including planning, delegation, safety constraints, and monitoring. Retrieval & vector-based systems , embeddings, structured reasoning, and semantic workflows. Ontology … engineering, or applied data engineering. Strong experience with LLMs, embeddings, RAG, retrieval stacks, and vector stores. Hands-on experience in multi-agent systems, agent orchestration, or MCP-like tool patterns. Proficiency in Python, including ability to build ...

design and build production-grade AI systems across: LLM applications using modern orchestration patterns, prompt frameworks, and evaluation loops. Multi-agent architectures , including planning, delegation, safety constraints, and monitoring. Retrieval & vector-based systems , embeddings, structured reasoning, and semantic workflows. Ontology … engineering, or applied data engineering. Strong experience with LLMs, embeddings, RAG, retrieval stacks, and vector stores. Hands-on experience in multi-agent systems, agent orchestration, or MCP-like tool patterns. Proficiency in Python, including ability to build ...

design and deploy sophisticated AI systems across multiple domains. This includes building LLM applications with robust orchestration, creating multi-agent architectures that handle complex workflows, and implementing advanced retrieval systems using vector databases and embeddings. You'll work on semantic … applied data systems. You have substantial hands-on work with LLMs, embeddings, retrieval architectures, and vector stores. Experience with multi-agent systems, orchestration frameworks, or tool-calling patterns is essential. Strong Python skills are required, along with experience deploying production systems ...

design and deploy sophisticated AI systems across multiple domains. This includes building LLM applications with robust orchestration, creating multi-agent architectures that handle complex workflows, and implementing advanced retrieval systems using vector databases and embeddings. You'll work on semantic … applied data systems. You have substantial hands-on work with LLMs, embeddings, retrieval architectures, and vector stores. Experience with multi-agent systems, orchestration frameworks, or tool-calling patterns is essential. Strong Python skills are required, along with experience deploying production systems ...

frameworks. Understanding of AI lifecycle: prompt engineering, agent workflows, deployment, and monitoring. Familiarity with LLMs and multi-agent systems. About Us: Ascendion is a leading provider of AI-first software engineering services. Our applied AI, software engineering, cloud ...

frameworks. Understanding of AI lifecycle: prompt engineering, agent workflows, deployment, and monitoring. Familiarity with LLMs and multi-agent systems. About Us: Ascendion is a leading provider of AI-first software engineering services. Our applied AI, software engineering, cloud ...

variety of domains. Some examples, but not limited to, are building a RAG leveraging open source or commercial LLMs, building a Multiagent system, leveraging Small Language models that could be locally resident, problems in computer vision, speech, Natural Language Processing (NLP), multilingual models, applied statistics, data mining ...

engineering early on. Strong communication skills and ability to guide product–engineering discussions. Nice to Haves Experience building agentic workflows, multi-agent systems, or autonomous LLM tools. Fintech domain exposure (not essential). This position do not provide visa sponsorship ...

engineering early on. Strong communication skills and ability to guide product–engineering discussions. Nice to Haves Experience building agentic workflows, multi-agent systems, or autonomous LLM tools. Fintech domain exposure (not essential). This position do not provide visa sponsorship ...