1 to 25 of 175 Permanent Model Context Protocol Jobs in London

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 with clients and internal teams effectively. Primary Skill Set Generative AI Expertise : Good understanding of modern Generative … Development Kit (ADK). Experience building agentic workflows with memory, state management, and reliable multi‐step task execution. Model Context Protocol (MCP) & Interoperability : Practical understanding of MCP for standardized, secure connectivity between LLMs/agents and external tools, data sources, and systems. Ability to build and consume ...

Generative and Agentic AI, including LLMs, retrieval-augmented generation (RAG), machine learning, and interoperability standards such as the Model Context Protocol (MCP). The role involves shaping the Generative AI strategy, selecting suitable models and technologies, and collaborating with cross‐functional teams to deliver customer‐centric, enterprise … ability to architect reliable agentic workflows with memory, state management and safe multi‐step task execution at scale. Model Context Protocol (MCP) & Interoperability – architectural knowledge of MCP for secure connectivity between LLMs/agents and enterprise tools, data sources, and systems; ability to build and govern MCP ...

prompt management solutions. Configure and secure API gateways for internally developed AI services and third-party integrations, including Model Context Protocol (MCP) connectors. Provision and maintain sandbox and staging environments to support rapid AI development and experimentation. Work closely with Information Security and Compliance teams to ensure … solutions Serverless inference Containerised AI workloads Model versioning and evaluation pipelines Experience configuring and securing API gateways and AI integration services. Understanding of MCP (Model Context Protocol) and modern AI connector architectures. Strong Infrastructure-as-Code experience using Terraform. Experience working with CI/CD pipelines ...

This capability is responsible for advancing Insulet’s AI enablement foundation through MuleSoft Anypoint Platform, MuleSoft AI Gateway, Model Context Protocol (MCP), MuleSoft Agent Fabric, API-led connectivity, event-driven integration, and secure agent-to-system orchestration. The role will help transform existing enterprise APIs and integrations … Security, Enterprise Architecture, SRE, and MuleSoft CoE teams to establish reusable agent-ready integration patterns. Enable secure access to enterprise systems and APIs through MCP servers, AI Gateway policies, governed API products, and reusable integration services. Support global delivery and follow-the-sun operational readiness for business-critical AI-enabled ...

measurable improvements: faster APIs, better performance, higher reliability AI Implementation & Automation (50%) Build AI‐Powered Development Infrastructure Implement Model Context Protocol (MCP) servers for service discovery, dependency mapping, and architecture compliance Create AI‐assisted CI/CD pipelines with automated code review, security scanning, and test generation … patterns, service decomposition, and legacy migration strategies AI/LLM Implementation (Critical Differentiator) Hands‐on experience building with Model Context Protocol (MCP) Demonstrated use of Claude Code, GitHub Copilot, or similar AI development tools in production work Experience implementing AI in CI/CD pipelines (code review ...

just report it, including the greenfield Organiser and Exhibitor Agentic products our founding Agentic team is building on Model Context Protocol (MCP). Your Role Own the architecture of Grip's platform-wide data and AI infrastructure — from how event data is captured and modelled … batch and streaming — with reliability and low latency at the core Own the data layer that underpins Grip's Agentic products, ensuring agents and MCP-based tools have access to clean, well-modelled, real-time data Define data contracts and standards that product squads (Engage, Manage) build against, working ...

abstract, it’s visible. In this role, you will: Lead the engineering of production-grade products and features for AI agents, including LLM proxies, MCP server orchestration, and A2A protocol governance. Translate the "agent-first" vision into robust technical solutions, leveraging our API and Event management pillars to provide …/ML concepts and how they intersect with API infrastructure - particularly AI agents, A2A protocol, and Model Context Protocol (MCP) - to inform technical direction AI at Gravitee is not about shortcuts - it is about working smarter, faster, and more sustainably at scale. Essential Skills A strong ...

governance, and delivery support. CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway. Rather than delivering individual business use cases end‐to‐end, the team enables product engineering groups across LSEG to expose knowledge, data, and actions … agents in a consistent, governed, and repeatable way. The team operates a Central MCP Delivery model: building critical MCP tools and services “for” product teams where required, while simultaneously defining standards, patterns, and platform capabilities that allow teams to progressively move towards self‐service contribution. LSEG AI Assist/ ...

limitations of live AI systems. Core AI Tech Stack : Absolute proficiency in Python , RAG architectures , and Vector Databases . Mastery of Context (MCP) : Deep understanding of MCP (Model Context Protocol/Master Control Prompts), including best practices and security guardrails for building useful assistants. Communication Skills … users. The Ultimate Metric : Your success is measured entirely on business impact-workflows automated, hours saved per week, and user adoption rates-not raw model benchmarks. Skills and Qualifications Benefits of working at Samsung include Hybrid working - 3 days in the office and 2 days at home per week ...

collaborative culture through communities of practice and emerging-technology events. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. Job Responsibilities Design, develop, and troubleshoot software solutions using creative … programming and database querying languages Experience with containerization Knowledge of agent‐to‐agent (A2A) communication concepts Familiarity with Model Context Protocol (MCP) Experience with agentic orchestrators, personal AI assistants, or AI skills development. We recognize that our people are our strength and the diverse talents they bring ...

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, tool‐use, and reasoning strategies for agentic systems. Stay technical. Contribute to architecture, critical‐path code, design reviews, and the hardest technical problems. … 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 success looks like in this ...

collaborative culture through communities of practice and emerging-technology events. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. Job Responsibilities Design, develop, and troubleshoot software solutions using creative … programming and database querying languages Experience with containerization Knowledge of agent-to-agent (A2A) communication concepts Familiarity with Model Context Protocol (MCP) Experience with agentic orchestrators, personal AI assistants, or AI skills development J.P. Morgan is a global leader in financial services, providing strategic advice and products ...

collaborative culture through communities of practice and emerging‐technology events. You will explore and operationalize emerging patterns such as agent‐to‐agent communication, model context protocols, and agentic orchestration, turning early‐stage concepts into scalable, production‐ready capabilities. Job Responsibilities Design, develop, and troubleshoot software solutions using creative … programming and database querying languages Experience with containerization Knowledge of agent‐to‐agent (A2A) communication concepts Familiarity with Model Context Protocol (MCP) Experience with agentic orchestrators, personal AI assistants, or AI skills development #J-18808-Ljbffr ...

experience designing and implementing multi‐agent architectures (task decomposition, coordination, orchestration, and agent‐to‐agent (A2A) interaction patterns) Model Context Protocol (MCP) & Integrations: Experience integrating agents with enterprise tools and data sources using MCP or equivalent context‐sharing patterns Knowledge Graphs & Reasoning: Building and leveraging knowledge … graphs for context enrichment, reasoning, and workflow automation RAG & Knowledge Systems: End‐to‐end RAG pipelines using enterprise search + vector stores (e.g., Elastic, Pinecone) with grounding, evaluation, and optimization Model Lifecycle & Governance: Model evaluation, monitoring, prompt/version control, and Responsible AI/MRM compliance Enterprise ...

communities and economies globally for more than 300 years. Through a comprehensive suite of trusted financial market infrastructure services - and our open-access model - we provide the flexibility, stability and trust that enable our customers to pursue their ambitions with confidence and clarity. OUR PEOPLE LSEG is headquartered … logging, observability, and LLM analytics. RAG, vector databases, and advanced retrieval techniques. LiteLLM as an AI and Model Context Protocol (MCP) gateway. MCP gateways and their integration with MCP servers. Contemporary AI models-including, as of July 2026, Fable 5, GPT-5.6 ...

Claude on Bedrock, Gemini, Azure OpenAI), selected per use case for quality, latency and cos t.Interfaces : Tools and Model Context Protocol (MCP) for integration; standards-based APIs and secure auth for client system s. What you'll doConceptualize fas t: embed with stakeholders, frame a business process … ve.Engineer the agent cor e: apply prompt engineering, context engineering, prompt caching, RAG/context-graph retrieval, memory, tool/function calling, MCP integration and multi-agent orchestrati on.Integrate to standard s: connect agents into client ecosystems through proven integration patterns, standards-based APIs and secure authenticati on.Make ...

rapid deployment of GenAI applications (including Retrieval-Augmented Generation (RAG) pipelines) and agents with planning, memory, and workflow orchestration Implement tools and frameworks for model versioning, experiment tracking, and lifecycle management Develop systems to monitor model performance and address data and model drift Recommend best practices … Familiarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP) Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK) Strong communication skills for both technical and non-technical audiences Preferred qualifications, capabilities ...

rapid deployment of GenAI applications (including Retrieval-Augmented Generation (RAG) pipelines) and agents with planning, memory, and workflow orchestration Implement tools and frameworks for model versioning, experiment tracking, and lifecycle management Develop systems to monitor model performance and address data and model drift Recommend best practices … Familiarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP) Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK). Strong communication skills for both technical and non-technical audiences. Preferred qualifications, capabilities ...

scalable, self-service solutions for documentation, SDKs, configurations, and pipelines to enable rapid deployment of GenAI applications and agents Implement tools and frameworks for model versioning, experiment tracking, and lifecycle management Develop systems to monitor model performance and address data and model drift Recommend best practices … Familiarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP) Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets Previous experience deploying and managing ML models Experience working ...

improve SEO, conversion rates, and user experience. Build production AI solutions using Vercel's AI SDK and AI Cloud—including conversational interfaces, production agents, MCP servers, and agentic workflows that transform customer operations. Embed with strategic customers to build production applications—working within their systems, understanding their constraints, and shipping … Core Web Vitals, with experience diagnosing and fixing LCP, CLS, and INP issues at scale. Have experience with Model Context Protocol (MCP), building MCP servers, or implementing complex tool‐use patterns in production AI applications. Have led enterprise AI transformation initiatives, including building production agents that automated ...

architecture of the subscription lifecycle, including sign-up, trials, plan changes, upgrades, downgrades, proration, pauses, cancellations and win-back. Define and evolve the entitlements model that connects a customer’s billing status with the content and services they can access across web, mobile and connected television platforms. … Legal. AI-enabled engineering Apply our standards for using large language models and agentic tools across software design, development, testing and operations. Treat specifications, context, prompts, agent configurations and evaluation criteria as version-controlled engineering artefacts. Design and improve guardrails, evaluations and quality gates for AI-assisted development ...

serve. • Engineer the agent core: apply prompt engineering, context engineering, prompt caching, RAG/context-graph retrieval, memory, tool/function calling, MCP integration and multi-agent orchestration. • Integrate to standards: connect agents into client ecosystems through proven integration patterns, standards-based APIs and secure authentication. • Make reusability … engineering bar, and grow the pod's agentic capability. Must Have Skills python LangGraph Open AI Agents SDK Model Context Protocol (MCP) Amazon Bedrock Large Language Models (LLMs ...

Large Language Model (LLM) integration and prompt engineering AI agents and agent orchestration Retrieval-Augmented Generation (RAG) Model Context Protocol (MCP) AI observability, experimentation and model evaluation Experience with cloud platforms, APIs, distributed systems and modern software engineering practices will help you succeed in this ...

infrastructure to accelerate AI solution development. Design and develop multi‐agent systems for orchestration, agent‐to‐agent communication, eval, memory, telemetry, and guardrails. Apply context and prompt engineering techniques to improve prompt‐based model performance. Develop and maintain tools and frameworks for prompt‐based agent evaluation, monitoring … with engineers, data scientists, and ML practitioners. Experience in customising and optimizing Github Copilot using VSCode Extension or Model Context Protocol (MCP). Experience with AWS and infrastructure‐as‐code tools such as Terraform. Experience in multi‐agent orchestration. Familiarity with MLOps practices, including CI/ ...

deliver. Develop prototypes and production components for client AI solutions: agent workflows, RAG pipelines, LLM integrations (Azure OpenAI, AWS Bedrock, Google Vertex, Anthropic), MCP-based tool integrations, and the governance and security controls around them. Deliver custom adapters and local tooling for regulated, cloud-restricted, or air-gapped environments where … leakage, agent permissioning, model and data security posture (AI-SPM/DSPM concepts). Familiarity with the Model Context Protocol (MCP), agent runtimes, or vector databases (e.g., Pinecone, Milvus, Weaviate, Chroma). Background in enterprise data governance, security, backup/resilience, or the Microsoft 365/ ...