1 to 25 of 364 Model Context Protocol Jobs in England

Generative and Agentic AI, LLMs, retrieval-augmented generation (RAG), machine learning, and modern interoperability standards such as the Model Context Protocol (MCP), along with a proven track record of architecting and implementing innovative, enterprise-scale solutions. As a Senior Architect/Consultant, you will play a pivotal … architect reliable agentic workflows with memory, state management, orchestration, and safe multi-step task execution at scale. Model Context Protocol (MCP) & Interoperability: Strong working knowledge of the Model Context Protocol (MCP) for standardized, secure connectivity between LLMs/agents and enterprise tools, data sources ...

frontend and backend services—from designing highly performant, intuitive modern user interfaces to building robust API services, Model Context Protocol (MCP) services, and autonomous AI agents. In this role, you will lead the architecture, design, and deployment of scalable Generative AI solutions, ensuring seamless integration into … both frontend and backend development, combined with hands-on experience building production-ready GenAI features. You will bridge the gap between backend APIs, custom MCP services, agentic workflows, and responsive modern user interfaces to deliver intelligent, automated planning experiences for our global customers. Your Impact Technical Leadership & System Architecture: Architect ...

that make Menlo's AI-driven features possible. The role blends deep systems and networking engineering with hands-on work on AI agents and MCP (Model Context Protocol) servers, alongside the cloud infrastructure (AWS, GCP, Kubernetes, Terraform, Linux) that supports them. You'll work alongside engineers across … against MARS roadmap milestones. Performance and stability of shipped Chromium-based components (e.g., crash rate, latency). Reduction in manual toil via agent/MCP-based tooling adopted internally. Code review turnaround time and quality for C++ contributions. Successful integration of AI agents or MCP servers into internal workflows ...

Cloud TokenHub—a unified AI platform providing access to leading Large Language Models (LLMs), AI Agents, and the Model Context Protocol (MCP) ecosystem—you will work closely with enterprise customers, Product, Engineering, Research, and Commercial teams to bridge business challenges with innovative AI solutions. Beyond solution delivery … business challenges, identify AI transformation opportunities, and design end-to-end AI and LLM solutions leveraging Tencent Cloud TokenHub, leading foundation models, AI Agents, MCP ecosystem, and enterprise AI capabilities. Lead technical discovery workshops, architecture design sessions, Proof-of-Concepts (POCs), technical validation, and production deployment planning to accelerate enterprise ...

context pipelines, leveraging chunking, hybrid search, re‐ranking, knowledge graphs and dynamic prompt construction. Building and consuming Model Context Protocol (MCP) servers to integrate enterprise tooling and shared capabilities. Maintaining production system reliability and supporting incident response for deployed AI agents. Providing technical guidance to junior … construction. Orchestration Frameworks: Hands‐on experience with agent orchestration frameworks (AWS Strands, OpenAI Agents SDK, Google ADK, DSPy, or raw API agent loops). MCP Integration: Practical experience with the Model Context Protocol (MCP), designing or consuming MCP servers. Evaluation & Memory: Experience implementing production evaluation frameworks ...

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 ...

large language models (LLMs) and generative AI concepts, including AI agents, prompt engineering, context management, and Model Context Protocol (MCP), including MCP Apps and their UI capabilities Mastery of AI tools, in particular Claude Desktop and Claude Code, with day-to-day use to work faster … agents, defining how each capability is exposed and packaged for agent-based consumption Recommend the best distribution channel for each business service, evaluating MCP, MCP App, and other options based on customer fit, reach, and technical trade-offs Build prototypes to test in front of internal and external clients, validating ...

large language models (LLMs) and generative AI concepts, including AI agents, prompt engineering, context management, and Model Context Protocol (MCP), including MCP Apps and their UI capabilities Mastery of AI tools, in particular Claude Desktop and Claude Code, with day-to-day use to work faster … agents, defining how each capability is exposed and packaged for agent-based consumption Recommend the best distribution channel for each business service, evaluating MCP, MCP App, and other options based on customer fit, reach, and technical trade-offs Build prototypes to test in front of internal and external clients, validating ...

Generative AI and Agentic AI using Google ADK . Design, develop and test AI Agents and work with Model Context Protocol (MCP) and MCP servers. Write high-quality code in Python and/or Java , working across modern AI and platform technologies. Provide technical leadership, mentoring … highly desirable. Experience with Generative AI and AI Agents , ideally including Google ADK . Practical experience with Model Context Protocol (MCP) and AI/data/service integration is highly desirable. Strong understanding of REST APIs, networking, databases and CLI tooling , with Postgres/Oracle experience preferred. ...

offs across performance, scalability, reliability, security, maintainability, and costDeep experience with system integrations and modern interoperability protocols, including Model Context Protocol (MCP) and agent-to-agent (A2A) standards, with the ability to define integration patterns and shape how these are adopted at scaleHands-on breadth across major … evolve the agentic workflows, skills, and tool-use integrations that allow AI systems to interact with Moody's platforms and third-party services via MCP and related protocols, and define the patterns other engineers build againstImplement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks ...

responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity. Skills and Competencies … ability to independently drive a product area Deep understanding of generative artificial intelligence, large language models, agentic artificial intelligence, and application programming interface or protocol-based products; direct exposure to Model Context Protocol or comparable agent-tooling protocols preferred Strong grasp of agile methodologies with experience ...

demonstrate the power of Zendesk headless technology and help customers embed Zendesk deep into their workflows inside and outside of the core platform via MCP and A2A technology. AI & Platform Architecture Autonomous Service Deployment: Master and deploy the Zendesk Agent Builder and Action Builder to architect multi-step, agentic workflows … target. Ecosystem Integration & Connectivity: Architect modern integrations connecting the Zendesk platform to external AI platforms and enterprise applications. Design these connections utilizing the Zendesk MCP (Model Context Protocol) Server, comprehensive APIs, and advanced Integration Platforms as a Service (iPaaS), while applying scalable enterprise integration patterns. Knowledge & Memory ...

agent workflows to support complex business and clinical use cases. Implement AI solutions using modern orchestration frameworks and Model Context Protocol (MCP). Design and develop scalable AI services and data processing solutions using Python and related technologies. Build and maintain Retrieval-Augmented Generation (RAG) solutions … multi-agent architectures and AI orchestration frameworks such as LangChain, Semantic Kernel, or AutoGen. Hands-on experience with Model Context Protocol (MCP) implementations. Strong understanding of vector databases and technologies such as Pinecone, Weaviate, FAISS, or Azure AI Search. Experience building and supporting Retrieval-Augmented Generation ...

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 ...

powered Production Intelligence platform. You will combine Site Reliability Engineering practices with modern agentic AI (reusable Skills, Model Context Protocol (MCP), and LLM tooling) to transform how engineering and leadership teams monitor, diagnose, and auto-remediate global SaaS infrastructure. What you'll do Technical Leadership & Architecture: Define … architecture for AI-assisted observability, automated incident response, and self-healing cloud infrastructure. Agentic Workflows & Tooling: Design and build production-grade AI agents, MCP tool integrations, and deterministic evaluation pipelines for automated operational decision support. Telemetry & Insights: Architect ingestion and correlation pipelines across distributed logs, metrics, OpenTelemetry traces, change events ...

incidents via telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails and security controls (SCPs/IAM boundaries … . Applying AI in CI/CD, observability, and incident response using AWS Bedrock/SageMaker and Model Context Protocol (MCP).Hands-on Agile delivery experience, actively participating in stand-ups and sprint ceremonies. Why Choose Fitch: Hybrid Work Environment: 2 to 3 days a week ...

incidents via telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails and security controls (SCPs/IAM boundaries … . Applying AI in CI/CD, observability, and incident response using AWS Bedrock/SageMaker and Model Context Protocol (MCP). Hands-on Agile delivery experience, actively participating in stand-ups and sprint ceremonies. Why Choose Fitch: Hybrid Work Environment: 2 to 3 days a week ...

LLMs, retrieval pipelines, agentic workflows, and platforms such as Anthropic Claude. Experience designing and deploying AI agents, leveraging Model Context Protocol (MCP), and orchestrating enterprise-grade AI solutions will be highly valued. Acting as a bridge between business and technology, you’ll work across product, data science … deploying agentic AI solutions using platforms such as Anthropic Claude, including AI agents, tool orchestration, reasoning workflows, Model Context Protocol (MCP), and enterprise-scale automation use cases. Hands-on experience building AI-enabled systems, such as LLM pipelines, document extraction, structured output generation, AI-assisted analytics, prediction ...

this role. Working with ML flow. Designing developing and testing agent build in Google ADK Working with Model Context Protocol (MCP) and creating servers. Other technology we use includes Neo4j, Postgres, Kafka and libraries such as FAST API. Build and maintain CI/CD pipelines to support … others can follow them. Generative AI: Familiarity with GenAI concepts including system prompts, Agent Development Kit (ADK), and Model Context Protocol (MCP) for data and service sharing. Google ADK: Hands‐on experience using Google ADK. Neo4j or other graph databases Team Leadership: Experience managing or coordinating software ...

design, build, and deliver next-generation AI-enabled applications and agentic systems. This role combines hands-on engineering across frontend applications, Python backend services, MCP infrastructure, agent workflows, and secure enterprise integrations. As an AI Engineer, you will build user-facing applications and backend services that integrate with Model Context Protocol (MCP) servers, LLM-based applications, RAG-based retrieval systems, and agent orchestration platforms. You will work closely with AI developers, platform engineers, product teams, and other stakeholders to deliver scalable, secure, observable, and production-ready AI solutions. This engineering role is suited for candidates ...

tools, retrieval systems and configurations for production use. Integrate AI systems with enterprise APIs, databases, applications and data platforms. Develop reusable connectors, APIs and Model Context Protocol tools. Build automated CI/CD, testing, configuration management and deployment workflows. Implement authentication, access control, secrets management, security … with Azure, AWS or Google Cloud, Kubernetes, Helm, Terraform and CI/CD technologies. Experience with LangGraph, AutoGen, smolagents or similar frameworks. Experience with Model Context Protocol, model‐serving platforms, vector databases and LLM gateways. Experience implementing AI evaluation, observability, tracing and performance monitoring. Experience with ...

patterns, 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/Internal MCP ...

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/ ...

optimize prompts and interaction strategies for LLMs to achieve desired outcomes in agentic systems. Integrate various tools, APIs, and data sources, potentially utilizing MCP Servers, to enhance model context and tool integration. Develop robust, scalable, and maintainable code in Python for all components of the agentic applications, from … translate requirements into technical solutions. Stay up-to-date with the latest research and developments in generative AI, LLMs, agentic systems, and protocols like MCP, evaluating their potential for our products. Contribute to the architecture and technical roadmap of our AI initiatives. Mentor junior engineers and share knowledge within ...

translate capability changes into delivery capability and commercial offerings. Building and Embedded Delivery Build production AI systems hands-on: agents, tool use, retrieval pipelines, MCP integrations and enterprise workflow connectors. Embed with client teams to map how work actually runs across functions, then design and deliver against it. Lead … Intellectual Property Own and productise Invoka's AI delivery IP: the accelerator framework, reusable components, prompt libraries and evaluation suites. Take our in-house MCP servers from internal tools to supported, documented, sellable asset, and own its roadmap. Develop our temporal data and change analysis capability, which we deliver ...