1 to 25 of 105 Multi-Agent System Jobs in London

opportunity to create scalable, safe, and reliable agentic solutions that transform how we work. We value your expertise in building multi-agent systems and your passion for collaborating across teams. At our company, you can grow your career, expand your skills … assistive AI agents that streamline complex workflows. You will collaborate with cross-functional partners to translate operational needs into robust multi-agent systems, leveraging advanced frameworks and technologies. Your work will directly impact our business by delivering scalable and reliable ...

take ownership of the architecture for enterprise AI capabilities, including: Agentic AI platforms, AI assistants, copilots and autonomous workflows Multi-agent systems incorporating reasoning, planning, memory, orchestration and tool integration Production-grade LLM and RAG architectures Intelligent search, knowledge assistants, workflow … operationalisation Strong executive stakeholder engagement and the ability to translate AI capabilities into measurable business outcomes Technology: Agentic AI & GenAI Multi-Agent Systems | Agentic AI Architecture | RAG | LLM Applications | Prompt Engineering | Responsible AI | AI Evaluation Frameworks LangChain | LangGraph | Semantic Kernel | AutoGen ...

Responsibilities Design and deliver enterprise-scale Agentic AI and Generative AI solutions Lead the architecture and implementation of autonomous and multi-agent systems Design AI-powered assistants, intelligent workflows and RAG-based solutions Collaborate with business and technology teams to integrate … grade AI solutions on AWS Strong knowledge of AWS Bedrock, Lambda, Step Functions and related services Experience designing AI agents, multi-agent systems and intelligent workflow automation Hands-on experience with RAG architecture and AI-powered assistants Knowledge of LangGraph ...

embedded directly within a cutting-edge AI research team, working on areas including large language models, reinforcement learning, synthetic data, multi-agent systems and AI agents , while also building the robust infrastructure needed to support complex research experiments. Non negotiable skills … ambiguous research environment where priorities can change rapidly. Experience with PyTorch, LLMs, LLM post-training, reinforcement learning, generative AI or multi-agent systems would be particularly valuable. A research-focused Master's or PhD in AI/ML is advantageous ...

with APIs, databases, external services and other software Experiment with different approaches to agent orchestration and multi-agent systems Build evaluation frameworks to understand how agents perform and continuously improve their reliability Work on agent … personal projects An understanding of concepts such as tool calling, RAG, agent orchestration, context management or multi-agent systems Strong problem-solving ability and the desire to work on technically difficult, ambiguous problems The ability to learn ...

software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This … -region HA/DR strategies, and CI/CD pipelines Agent Engineering & Development : Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive ...

both API-based (e.g., Claude, GPT, Gemini) and open-source (e.g., Llama, Mistral) LLM-based solution design. Agentic AI & Multi-Agent Architecture: Deep expertise designing autonomous and multi-agent systems that reason, plan … Generative and Agentic AI architectures that encompass data preprocessing, model selection, RAG pipelines, agent orchestration, MCP-based tool and system integration, guardrails, training/inference pipelines, and deployment strategies. Strong grasp of scalable, reliable, secure, and cost- and latency-efficient system design ...

knowledge management, and workflow automation. Architect advanced retrieval using RAG, Agentic RAG, Graph RAG, knowledge-graph, and hybrid approaches. Design multi-agent systems with modern orchestration and reasoning architectures, including human-in-the-loop and autonomous frameworks. Define memory, context, planning … CrewAI, AutoGen, DSPy, Semantic Kernel, Strands. Advanced retrieval : Graph RAG, knowledge graphs, context graphs, hybrid search, vector databases. Agentic patterns : multi-agent architectures, planning and reasoning, MCP (Model Context Protocol). Model customization: fine-tuning, distillation, and model evaluation at scale. What ...

metrics. This role requires strong technical expertise across Generative and Agentic AI—including LLMs, retrieval-augmented generation (RAG), autonomous and multi-agent systems, and modern interoperability standards such as the Model Context Protocol (MCP)—coupled with excellent communication skills to engage ...

performance metrics (latency, accuracy, cost)Exposure to monitoring/observability tools for production systems Nice to Have: Experience with multi-agent systems or distributed AI architecturesExperience optimising LLM usage across multiple providers (cost/performance trade-offs)Familiarity with vector … Contract | + ExtensionsHybrid | London Company: Experis UK Level of experience (years): Senior (5+ years of experience) Tagged as: Industry, Machine Learning, NLP, Recommendation System, United Kingdom #J-18808-Ljbffr ...

Azure OpenAI Anthropic Google Gemini Model selection and benchmarking Prompt engineering Fine-tuning and model customisation where appropriate Agentic AI Multi-agent systems Tool calling Function orchestration Workflow automation Planning and reasoning patterns Human-in-the-loop design Knowledge & Retrieval ...

translate complex forecasting models and machine learning algorithms into production-ready, scalable architectures. Design robust observability and evaluation frameworks for GenAI systems, including system guardrails, continuous monitoring, and optimisation mechanisms. Your Skills Experienced background in software architecture, highlighted by a dedicated and deep focus on designing, scaling …/ML systems. Deep expertise in LLM architecture, prompt engineering, and GenAI application design, paired with a strong understanding of multi-agent systems and autonomous decision-making frameworks. Highly proficient in Python programming with hands-on experience using modern AI/ ...

SKILLSExperience leading teams building AI products for financial services, capital markets, research, analytics, or other data-intensive domains. Experience developing multi-agent systems, autonomous workflows, copilots, and intelligent AI assistants. Knowledge of reinforcement learning, fine-tuning, synthetic data generation, model compression ...

stakeholder management skills. Bonus/Good to Have Enterprise AI: Experience implementing enterprise AI platforms, intelligent automation, AI copilots, multi‐agent systems, or AI workflow orchestration. Industry Consulting: Experience working with customers across financial services, healthcare, manufacturing, retail, public sector ...

leading teams building AI products for financial services, capital markets, research, analytics, or other data‐intensive domains. Experience developing multi‐agent systems, autonomous workflows, copilots, and intelligent AI assistants. Knowledge of reinforcement learning, fine‐tuning, synthetic data generation, model compression ...

like Prometheus, Grafana or DatadogExperience with distributed systems, scaling, and both SQL and NoSQL datastoresAgentic workflow experience (autonomous or multi-agent systems) is a plus, and this AI Engineer role suits someone fluent in English to C2 levelBenefits: Real ownership ...

regulatory considerations into scalable, production-ready AI architectures. Design and implement advanced GenAI solutions, including: Retrieval-Augmented Generation (RAG) Multi-Agent Systems Knowledge Management Platforms Enterprise Workflow Automation Define architecture patterns, governance standards, security controls, and best practices for enterprise ...

Technical Builder who designs, constructs, and deploys enterprise-grade agentic AI solutions directly inside customer environments. AFO powers the multi-agent orchestration layer, transforming messy operational workflows, unstructured data (emails, PDFs, spec sheets), and legacy ERP logs into autonomous execution engines with … broader enterprise technology landscape. You will write production code, architect real-time data grounding systems, perform prompt engineering, manage multi-agent communication protocols, and deploy automated supply chain and back-office workflows into production from day one. What You'll Actually ...

using data, CCaaS platforms and AI to create seamless and consistent experiences Contribute to building and delivery of RAG pipelines, multi-agent orchestration and eval frameworks for enterprise-scale AI deployments Be a technical advisor Support client teams on AI architecture decisions … background with production experience in Python and similar languages across AI systems Experience building or contributing to RAG pipelines, multi-agent systems or LLM-based products, ideally at meaningful scale Hands-on experience with at least one major cloud ...

ownership from architecture and prototyping through to deployment, monitoring and continuous evaluation. Key responsibilities: Design and deliver production GenAI and multi-agent systems Build agentic workflows, RAG solutions, tool use and multi-step orchestration Define evaluation strategies … CrewAI or similar Experience with AWS, particularly Bedrock, Lambda, ECS, EKS or SageMaker Strong understanding of RAG, agentic AI and multi-agent architectures Experience with CI/CD, cloud infrastructure and application deployment Comfortable working directly with clients and senior stakeholders Experience ...

ownership from architecture and prototyping through to deployment, monitoring and continuous evaluation. Key responsibilities: Design and deliver production GenAI and multi-agent systems Build agentic workflows, RAG solutions, tool use and multi-step orchestration Define evaluation strategies … CrewAI or similar Experience with AWS, particularly Bedrock, Lambda, ECS, EKS or SageMaker Strong understanding of RAG, agentic AI and multi-agent architectures Experience with CI/CD, cloud infrastructure and application deployment Comfortable working directly with clients and senior stakeholders Experience ...

influence architecture decisions and work effectively across multidisciplinary teams Preferred Qualifications, Capabilities, and Skills Experience designing or operating multi‐agent systems, agent orchestration frameworks, workflow automation platforms, or tool‐augmented LLM applications Experience with context engineering techniques ...

output and productivity. Identify bottlenecks, repetitive work and opportunities where technology could fundamentally change how the work gets done. Multi-Agent Development: Design and deploy multi-agent systems where distinct AI personas collaborate … video/audio APIs, social publishing APIs, creative tools and platforms, and logistics trackers. Guardrails & Reliability: Design robust human checkpoints. Ensure the AI system fails gracefully, asks for human clarification when unsure, and, for example, never hallucinates brand guidelines or publishes without approval. Data & Infrastructure: Implement data retention ...

Responsibilities: Architect, develop, and productionize autonomous and assistive AI agents to enhance operations. Design multi-agent systems, including role definition, tool integration, planning, memory, and workflow orchestration using modern agent frameworks. Implement Retrieval-Augmented Generation (RAG) pipelines … create scalable, safe, and reliable agentic solutions that transform how we work. We value your expertise in building multi‐agent systems and your passion for collaborating across teams. At our company, you can grow your career, expand your skills, and make ...

leadership and architectural direction to our AI engineering team. In this role, you will be responsible for designing high-performance multi-agent systems, establishing robust evaluation standards, and mentoring other engineers to build production-grade, LLM-backed applications. Requirements 5+ years … Reduction: Designing deterministic verification loops for enterprise outputs to guarantee factual reliability. Latency Optimization: Cutting round-trip time across complex, multi-agent workflows to achieve real-time responsiveness. Governance Automation: Building “Policy Agents” that turn static regulatory policies into real-time, automated ...