1 to 25 of 57 Permanent Multi-Agent System Jobs in London

embedded with the client, turning ambiguous business problems into production agents, fast. Your deliverable is Business Transformation Agents: autonomous and multi-agent systems that automate and reimagine real business processes such as invoice disputes, procurement approvals, onboarding, claims and compliance workflows. … ks.Build Business Transformation Agent s: design and ship single-agent and multi-agent systems in Python using ADKs that automate and transform real client workflows, with measurable R OI.Own efficiency as the scorecar ...

embedded with the client, turning ambiguous business problems into production agents, fast. Your deliverable is Business Transformation Agents: autonomous and multi-agent systems that automate and reimagine real business processes such as invoice disputes, procurement approvals, onboarding, claims and compliance workflows. … prototype in days, not weeks. • Build Business Transformation Agents: design and ship single-agent and multi-agent systems in Python using ADKs that automate and transform real client workflows, with measurable ROI. • Own efficiency ...

yours.Responsibilities: Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI). Architect and code the connective tissue between Google … Architecture* Enterprise AI Solutions* AI System Architecture* Google Cloud Platform (GCP)* Technical Discovery Sessions* French (Fluent)* German (Fluent)* Multi-agent Systems* LangGraph* CrewAI* ADK* ReAct* Self-reflection* Hierarchical Delegation* Post-sales* Technical Consulting* Large Language Model (LLM) Metrics* State ...

lead developer embedded within customer accounts, for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) Architect and code the connective tissue between Google’s AI products and customer's live infrastructure … unstructured data using both vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise AI solutions. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and patterns (e.g., ReAct, self-reflection, hierarchical delegation). Knowledge ...

with customers. Preferred qualifications: Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation). Experience … yours. Responsibilities Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI). Architect and code the connective tissue between Google ...

technical discovery sessions. Preferred qualifications: Master’s or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation). Knowledge … granular tracing. Responsibilities: Serve as a developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol (MCP) servers) that drive measurable return on investment (ROI). Architect and code the \"connective ...

local stakeholders. Preferred qualifications: Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation). Experience … yours. Responsibilities Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI). Architect and code the connective tissue between Google ...

local stakeholders. Preferred qualifications: Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation). Experience … yours. Responsibilities Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI). Architect and code the connective tissue between ...

demand production systems with measurable ROI, governance, and scale, and most stall in the gap between an impressive pilot and a system that survives production. EXL lives in that gap. We are accountable for outcomes on our clients’ data, in their environment, against their SLAs. This role … 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 ...

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 … Claude, GPT, Gemini) and open‐source solutions (Llama, Mistral). Agentic AI & Orchestration : Hands‐on experience designing autonomous and multi‐agent systems that reason, plan, and act using tools. Familiarity with agentic design patterns (ReAct, planning, reflection, human‐in‐the‐loop ...

solution design. Agentic AI & Multi‐Agent Architecture – design of autonomous and multi‐agent systems, agentic design patterns (ReAct, planning, reflection, tool use, human‐in‐the‐loop), and frameworks (LangGraph, CrewAI, MAF, OpenAI Agents ...

testing and debugging, while learning from top technologists through design sessions and peer code reviews. Furthermore, you'll benefit from a comprehensive support system: you'll join a cohort of new hires, embarking on a shared journey to master our company culture, tools, processes, and the technical proficiencies … house Gemini) Large Language Models (LLMs): Gemini, OpenAI, Claude, Llama, Local Models Frameworks: LangChain, LlamaIndex, Hugging Face Orchestration: LangGraph, Multi-Agent Systems Development Languages: Java, PythonFastAPI Retrieval-Augmented Generation (RAG): PostgreSQL, Vector DBs, Advanced Retrieval ML/DL Frameworks: PyTorch, TensorFlow ...

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 ...

clients, with a proven track record of taking AI use cases from concept to production Strong understanding of AI agents, multi-agent systems, LLM orchestration, agent frameworks, RAG, MCP, AI governance, observability, and production-grade AI architectures ...

multi‐agent systems. Working familiarity with enterprise IT architecture, cloud platforms (AWS, Azure, GCP), and system integration patterns. Consulting & Client Skills High agency; comfortable navigating ambiguity, working across complex organisations, and contributing without a well‐defined playbook. Strong communication skills ...

hands‐on technical leadership experience at Principal/Lead level. Strong expertise in Generative AI, LLMs, agentic architectures, and multi‐agent systems with proven production delivery in regulated environments (FS preferred). Proven experience building agentic solutions using Microsoft Copilot Studio ...

execute enterprise-wide, reusable AI/ML frameworks and core infrastructure to accelerate AI solution development. Design and develop multi-agent systems for orchestration, agent-to-agent communication, eval, memory, telemetry, and guardrails. … field. Experience in machine learning engineering. Strong proficiency in Python and experience deploying end‐to‐end pipelines on AWS. Hands‐on experience in system design, application development, testing, and operational stability. Preferred qualifications, capabilities, and skills: Strategic thinker with the ability to drive technical vision for business impact. ...

enterprise-grade RAG (Retrieval-Augmented Generation) systems, including context engineering and multimodal data pipelines. Design and deployment of autonomous multi-agent systems using modern orchestration frameworks and evaluation approaches. Experience delivering Text-to-SQL solutions and natural language interfaces ...

external customer projects. Preferred qualifications Master’s or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks like ReAct and self-reflection. Experience debugging Agent logic and optimizing tool … lead developer for complex Conversational AI and CX applications, transitioning from rapid prototypes to production‐grade agentic workflows (e.g., multi‐agent systems, Model Context Protocol (MCP) servers) that drive measurable return on investment. Architect and code conversational flows that ...

Vision We are building a next-generation system that reimagines banking workflows for our Corporate, Commercial, and Investment Bankers. Our vision is to empower them with a revolutionary Agentic AI Platform, featuring intelligent, autonomous agents that streamline processes, uncover new opportunities, and deepen client relationships—ultimately leading … Agentic Frameworks: Deep expertise in building production‐grade agentic systems using GCP as primary (ADK, Vertex AI) Multi‐Agent Systems: Hands‐on experience designing and implementing multi‐agent architectures (task decomposition, coordination ...

your domain and across the broader AI architecture - ensuring cohesion across the full system. This includes architecting AI agents encompassing multi-agent orchestration, tool use, skills use, and memory systems, as well as the integration of fine-tuned foundation models … process, evaluating build-vs-buy decisions for AI platforms (e.g., Arize, LangSmith) and foundational models. Architect model- and tool-agnostic multi-agent systems governed by an MCP Control Plane. Design and implement the Agent Registry ...

shared belief that exceptional people are the foundation of everything great we'll build. The Role We're building a learning system that teaches AI agents how enterprises actually work. Our system ingests knowledge bases, conversations, tickets, and system logs, then produces written instructions … want to work directly with our enterprise customers. Whether you've scaled LLM workflows handling millions of requests, built multi-agent systems in production, or designed evaluation frameworks for enterprise deployments, we want people who bring intensity and self-direction ...

, prioritizing context engineering, transparency, and explainability to foster user trust. Ability to design end‐to‐end secure, observable multi‐agent systems using complex design patterns (ReAct, self‐reflection, etc.), state management, and tool‐calling protocols. About ...

will be a hands-on AI builder PM at the centre of that shift. You will prototype and ship multi-agent systems that automate the merchandising experiment lifecycle end to end, define the trust and governance patterns that let agents … topics accessible and to drive alignment across senior cross-functional stakeholders. Preferred Qualifications: Experience building or shipping agentic AI systems: multi-agent orchestration, tool/function calling, MCP or similar protocols, agent memory, human-in-the-loop ...

solve real-world problems using AI. Passion for emerging AI technologies and continuous learning. Desirable Experience RAG (Retrieval-Augmented Generation) Multi-Agent Systems Context Engineering AI Evaluation Frameworks Human-in-the-Loop Systems AI-Native Development Learning technologies or educational ...