1 to 25 of 66 Model Context Protocol Jobs in the UK

Cutting-Edge Tech Stack: Experiment with the latest LLMs, architect RAG implementations, design sophisticated agentic systems, and develop Model Context Protocol (MCP) servers. Enterprise Scale: Build GenAI solutions across multiple business units while creating unified patterns and reusable component frameworks. Dynamic Culture: Work at the intersection … environment. We'll Count on You To Lead GenAI Development: Spearhead the creation of enterprise chatbot platforms, evaluation frameworks, agentic workflows, RAG architectures, and MCP implementations. Pioneer Innovation: Act as a hands-on engineer bridging the gap between research breakthroughs and production-ready capabilities to generate tangible business value. Build ...

engineering teams at the company. Your role is pivotal in shaping the architecture of our Model Context Protocol (MCP) servers, security controls and plugin ecosystem. This is an opportunity to solve complex challenges, develop practical agentic tooling being used at an enterprise scale and deliver work that … Python and TypeScript. AI Tooling & Ecosystems: Proven experience or strong understanding of AI development tools (like Claude Code), Model Context Protocol (MCP), LLM integration and prompt engineering. Cloud & DevOps: Hands‐on experience with cloud platforms (GCP, AWS), containerization (Docker, Kubernetes) and modern CI/CD practices. Frontend ...

across a Microsoft technology stack. You will work closely with software engineers, data specialists, and product teams to integrate Azure AI, Microsoft CoPilot, and Model Context Protocol into existing business systems. While experience with C# and .NET would be highly beneficial, it is not essential … ecosystem Strong understanding of APIs, data flows, and application architecture Experience of .NET and C# development is desirable but not essential Familiarity with CoPilot, Model Context Protocol, or similar AI technologies Excellent problem-solving, communication, and collaboration skill This role offers the opportunity to take ownership ...

problems. They're hiring a Principal Platform Engineer to own the design and delivery of a suite of Model Context Protocol (MCP) servers - the trusted, governed gateway between AI agents and their core payments platform. This is a hands-on principal role. You'll set technical direction … write production code, not just review it. What you'll be doing: Owning the architecture and delivery of MCP servers that expose platform data and capabilities to AI agents and internal developer tooling Designing the transport and session model (Streamable including stateful sessions for progress streaming, subscriptions, sampling ...

agent interaction Drive the application of GenAI to modernise, refactor, and accelerate legacy systems Define and implement APIs, contracts, and metadata aligned with the Model Context Protocol Shape and evolve internal tooling that supports AI-native SDLC workflows Influence architecture decisions, conduct design and code reviews … with experience delivering complex, high-scale systems Ability to mentor, guide, and upskill engineers within the team Familiarity with or eagerness to advance in: Model Context Protocol for managing context and tool interfaces for agents LLM integration patterns including prompt orchestration, multi-agent planning and tool ...

Senior Software Engineer MCP/AI Tooling Really exciting Senior Software Engineer role to help build a new generation of AI-native developer infrastructure. This role focuses on designing and building Model Context Protocol (MCP) servers and tooling that securely expose platform capabilities to AI agents, internal … enable large language models and agentic systems to interact safely, reliably, and effectively with real production environments. What Youll Be Doing Design and build MCP servers, tools, and integrations Develop secure APIs and services for AI agents and internal tooling Implement authentication, session handling, streaming, and stateful interactions Help define ...

within approximately six months from project start. Solutions may use a wide range of approaches, including agentic systems, model context protocol (MCP) servers, retrieval augmented generation (RAG), classical machine learning, knowledge graphs, data transformations, and business logic. The emphasis is on solving the right problem rather than … data-driven solutions • Excellent knowledge of Python and core data science libraries such as pandas, scikit-learn, LangChain, etc. • Experience with LLMs, including foundation model APIs, prompt engineering, and retrieval augmented generation • Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative ...

Integrate Azure AI services (Azure OpenAI, Cognitive Services, Azure ML, AI Search) into production applications. Build and refine LLM-powered features, agentic workflows, and MCP (Model Context Protocol) integrations. Collaborate with clients to understand requirements and translate them into working software. Contribute to technical research, prototyping … development. Familiarity with AI-assisted development tools such as GitHub Copilot, Claude, and Cursor. Azure AI Engineer certification or equivalent practical experience. Understanding of MCP, RAG architectures, or vector databases. Benefits Industry-leading training and development opportunities. Competitive salary with progression potential. 23-days holiday allowance, increasing with length ...

through governed semantic and knowledge layers. The industry is at an inflection point. Google Cloud’s Agentic Data Cloud, BigQuery Graph, Knowledge Catalog, and MCP‐native database tooling are redefining how data platforms serve autonomous agents. We need a technical leader who understands this shift deeply—not as a trend … governed semantic layers. Agentic Data Platform. Architect the infrastructure that enables AI agents to discover, reason over, and act on enterprise data. This includes MCP‐based tool connectivity, agent‐facing data services, and integration with emerging capabilities such as BigQuery Graph, Knowledge Catalog, and the Google Cloud Data Agent Kit. ...

agents through governed semantic and knowledge layers.The industry is at an inflection point. Google Cloud’s Agentic Data Cloud, BigQuery Graph, Knowledge Catalog, and MCP-native database tooling are redefining how data platforms serve autonomous agents. We need a technical leader who understands this shift deeply—not as a trend … from governed semantic layers.Agentic Data Platform. Architect the infrastructure that enables AI agents to discover, reason over, and act on enterprise data. This includes MCP-based tool connectivity, agent-facing data services, and integration with emerging capabilities such as BigQuery Graph, Knowledge Catalog, and the Google Cloud Data Agent Kit.Advanced ...

Role Context the company is a private-equity backed platform business supporting over $6 trillion of assets globally, with deep, long-standing relationships across the asset and wealth management ecosystem. Private markets are rapidly becoming a core part of wealth portfolios – but the industry infrastructure has not kept pace. … indexing, retrieval pipelines, grounding, and evaluation. Agentic patterns and orchestration frameworks – multi-step workflows, tool use, evaluation loops. Model Context Protocol (MCP) and similar integration patterns for connecting LLMs to real data and services. Prompt design, model evaluation, and the practical trade-offs of LLM systems ...

platforms (e.g. Claude, GPT), including an understanding of capabilities, trade-offs, and enterprise adoption Working knowledge of Model Context Protocol (MCP) and agentic AI architectures, with experience integrating AI securely and at scale Practical experience in enterprise AI governance, prompt engineering, and deployment approaches (including RAG, fine ...

platforms (e.g. Claude, GPT), including an understanding of capabilities, trade-offs, and enterprise adoption Working knowledge of Model Context Protocol (MCP) and agentic AI architectures, with experience integrating AI securely and at scale Practical experience in enterprise AI governance, prompt engineering, and deployment approaches (including RAG, fine ...

level execution and processing platform that enables private market investments to be delivered at managed‐account scale, with the same operational discipline and integration model that wealth managers expect in public markets. This is a senior engineering hire into the PMN team. You will contribute to the build … indexing, retrieval pipelines, grounding, and evaluation. Agentic patterns and orchestration frameworks – multi‐step workflows, tool use, evaluation loops. Model Context Protocol (MCP) and similar integration patterns for connecting LLMs to real data and services. Prompt design, model evaluation, and the practical trade‐offs of LLM systems ...

related field, with demonstrable work shipped to production. Strong proficiency in Python and SQL; comfortable working across the data stack from ingestion pipelines to model inference layers. Experience designing and building data lakes or lakehouses, including schema design for heterogeneous structured and unstructured data sources (documents, PDFs, images, tabular … multi‐agent workflows, with awareness of orchestration patterns, tool use, and failure modes in agentic systems. Familiarity with Model Context Protocol (MCP) or analogous tool‐serving frameworks for connecting language models to live data sources and internal APIs. Strong grasp of data quality practices, including lineage tracking ...

live at scale in enterprise with room to grow. Malcolm is in production with Aviva for Home and Life insurance, operating through MCP (Model Context Protocol) and 1st party chat experiences. We have a small engineering team, a clear technical roadmap, and a founder who has deep … lead the engineering team (currently 1-3 engineers), hiring deliberately as the roadmap demands. Work directly with insurer partners on integrations - the commercial context matters here and you’ll be in those conversations. Be a genuine co-founder partner to the CEO: product strategy, commercial decisions, fundraising narrative. ...

guide integration patterns between applications, platforms, and AI services Make pragmatic decisions about when and how emerging AI integration approaches (e.g. protocols such as MCP) should be adopted Work closely with architects, product teams, data scientists, and platform engineers to deliver end-to-end solutions Ensure solutions meet standards … production environments Desirable experience: Integrating software systems with AI platforms or AI-enabled services Exposure to emerging AI integration patterns or protocols (e.g. Model Context Protocol) Platform engineering or DevOps at scale Experience working in regulated or security-conscious environments Defining technical standards or architectural direction across ...

guide integration patterns between applications, platforms, and AI services Make pragmatic decisions about when and how emerging AI integration approaches (e.g. protocols such as MCP) should be adopted Work closely with architects, product teams, data scientists, and platform engineers to deliver end-to-end solutions Ensure solutions meet standards … production environments Desirable experience: Integrating software systems with AI platforms or AI-enabled services Exposure to emerging AI integration patterns or protocols (e.g. Model Context Protocol ) Platform engineering or DevOps at scale Experience working in regulated or security-conscious environments Defining technical standards or architectural direction across ...

infrastructure, data pipelines, orchestration layers, integration patterns, and governance controls. Develop reference architecture for agentic AI systems and multi‐agent workflows, establishing standards for MCP and model‐context protocols. Create AI reference architectures for investment and front‐to‐back office use cases. Drive integration of AI capabilities with … core data platforms and content platforms, leveraging RAG and MCP to unlock proprietary data assets. Governance & Risk: Design and operationalize AI governance, covering model risk management, explainability, bias monitoring, data lineage, and regulatory compliance. Evolve model evaluation and selection criteria for frontier and open‐weight models, balancing capability ...

baseline requirement, not a differentiator Python and/or Java for backend service development LLM integration experience – OpenAI, Anthropic, or equivalent APIs MCP, REST APIs, Microservices Architecture Cloud platforms – AWS, Azure, or GCP Preferred Agentic framework experience – LangChain, LangGraph, AutoGen, or similar RAG pipeline design and vector database experience (Pinecone ...

Mosaic AI, MLflow 3.0, and Unity Catalog Designing multi-agent systems with LangGraph, CrewAI, AutoGen, Semantic Kernel, and Bedrock Agents Defining enterprise standards for MCP servers, A2A communication, and agent-to-system interoperability Owning Responsible AI guardrails aligned to NIST AI RMF, EU AI Act, and ISO/ ...

from monolithic to microservice architectures Experience deploying or governing enterprise AI tooling (Claude Enterprise, Copilot, or similar), particularly around secure rollout, usage policies, and MCP integrations What We Offer Opportunity to shape and own the technical infrastructure Small, collaborative team environment where your expertise will have a direct impact Opportunity ...

efforts. You are someone with the scar tissue of running agents in production. You have strong, reasoned opinions on emerging open standards (such as MCP, A2A, and ACP) and deep expertise in complex architectural patterns like durable execution and agent memory. You are passionate about building a world‐class developer ...

analysis tools such as Matlab Simulink (e.g. optimisation and ML toolboxes), PySpark and Jupyter notebooks. Work on projects on areas such as agentic AI, MCP, RAG, generative AI, trust and security, driving innovations from concept through PoC to MVP. Experience with semantic web technologies; RDF, OWL, knowledge graph and ontologies ...

architectures. Proven experience designing and executing customer pilots and proofs of concept that demonstrate business value. Deep understanding of AI technologies (LLMs, ChatGPT, NLP, MCP automation frameworks) and their practical applications in CX. Expertise in one or more of the following domains: CCaaS, Customer Service software, ITSM, Business Intelligence, Workforce ...