1 to 25 of 32 Permanent Model Context Protocol Jobs in London

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 ...

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/ ...

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 customizing and optimizing GitHub Copilot using VSCode Extension or Model Context Protocol (MCP). Experience with AWS and infrastructure-as-code tools such as Terraform. Experience with multi-agent orchestration. Familiarity with MLOps practices, including CI/ ...

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 ...

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 ...

including an understanding of capabilities, trade offs, and enterprise adoption./li li We need working knowledge of Model Context Protocol (MCP) and agentic AI architectures, with experience integrating AI securely and at scale./li li We need practical experience in enterprise AI governance, prompt engineering ...

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 ...

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. ...

build, and deploy scalable, cloud-native, AI-powered data-driven products in AWS Drive the integration of AI, automation, agents, and modern tooling (including model context protocol capabilities) to enhance developer productivity and delivery pipelines Lead and develop team members across software, data, platform ...

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/ ...

Sound judgement around data access, PII handling, RBAC, and the security implications of letting AI systems act autonomously. Preferred experience Familiarity with agentic patterns (MCP, RAG, evaluation frameworks) and the maturity to know when a simpler approach beats a more sophisticated one. Experience in a scale‐up, SaaS, or other ...

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 ...

native services (e.g., serverless, containerization, managed AI/ML platforms) and CI/CD pipelines for accelerated delivery. Implement robust MLOps practices to streamline model deployment, monitoring, and lifecycle management in cloud environments, including data versioning, feature store integration, and data pipeline management. Business Partnership & Solution Architecture: Collaborate closely … systems: Design and implement tool‐calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol. Integrate with runtime ecosystems: Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post‐incident summarization with ...

made architecture decisions at meaningful scale, so has a profile that evidence of that kind of decision making. AI as core leverage - LangChain, LangGraph, MCP, Claude Code, spec-driven development, prompt versioning at production etc., rather than just using AI as a productivity tool. Whats on Offer Opportunity to shape ...

Experience building and deploying AI products into production environments Python and modern backend engineering experience Experience with LLMs, RAG architectures and agentic AI systems MCP or similar protocols for connecting AI systems with tools and external services Strong product thinking and commercial awareness Experience operating within high-growth, scale ...

Experience building and deploying AI products into production environments Python and modern backend engineering experience Experience with LLMs, RAG architectures and agentic AI systems MCP or similar protocols for connecting AI systems with tools and external services Strong product thinking and commercial awareness Experience operating within high-growth, scale ...

practices DevOps (CI/CD, Pipelines, Infrastructure-as-Code) Experience managing a team of developers Exposure to Agentic AI patterns (tool use, orchestration frameworks, MCP, or similar) Familiarity with modern UI frameworks and tooling (React, React Native, npm) Experience working with Azure DevOps build and release pipelines Core Values ...

stakeholder leadership, with the credibility and communication skills to operate at C-suite level.## Desirable* Working knowledge of agentic AI, including LLMs, RAG and MCP architectures, sufficient to set direction and challenge a technical delivery team.* Experience with voice AI platforms such as ElevenLabs, Vapi, Retell or equivalent.* Experience working ...

Amazon Bedrock and SageMaker Claude/Anthropic Azure AI Foundry or Azure OpenAI Databricks Vector databases and RAG architectures Agentic AI orchestration frameworks and MCP servers Model and data lifecycle management Desirable Experience Experience working within public sector or regulated environments Experience with secure government delivery environments Experience contributing ...

product requirements, and to provide early, high‐level advice on opportunities and possible solutions. Stay current with emerging AI trends, technologies, protocols, research breakthroughs, model development and AI software design pattern and best practices. Provide technical guidance and mentorship to the engineering teams. Collaboration and Communication Foster strong relationships … focus in AI/ML domains. Proven experience designing and deploying AI solutions using frameworks such as LangChain, RAG, and vector databases or the MCP protocol. Deep understanding of LLMs, prompt engineering, model evaluation, and fine‐tuning strategies. Strong proficiency in ML frameworks (e.g., TensorFlow, PyTorch) and cloud platforms ...

audiences. Support regional and service line data teams to promote adoption and identify high‐value use cases. Design and delivery of technical integrations, including MCP server, enterprise data catalog, analytics tools, and Semantic Layer, knowledge graph platforms such as PoolParty (Graphwise). Education & Experience Undergraduate degree, preferably in computer science ...

process at varying customer scales, and expertise in associated migration utilities, and hybrid SaaS and on-premise deployment models Experience with Rovo, Agentic AI, MCP, and/or other AI integrations You're fluent in English. Due to a strong customer presence in the DACH region, professional-level German communication ...

want to talk to you! Responsibilities Understand Agent Interoperability – Map and integrate external agents from hyperscalers (e.g., Copilot, Gemini) into Agentforce via open standards (MCP, A2A); design how these systems collaborate. Enable Conversational & Background Agents – Use Agentforce Studio and Agent Builder to configure chat and background agents; integrate with external … frameworks, sharing insights, and experimenting with cutting‐edge technologies. Preferred Qualifications Advanced Integration – Experience integrating Salesforce with external agents via APIs and open standards (MCP, A2A). Governance & Observability – Familiarity with prompt governance, observability, monitoring frameworks, responsible AI and compliance best practices. Cross‐Platform Background – Background in cross‐platform integrations ...

multi-agent system on AWS, orchestrating multiple AI providers across signal generation, content, and research workflows, and is exposed to clients through their own MCP server. What We're Looking For We are seeking an AI Engineer to help shape the technical direction of the AI platform. You will design … execution loop, tool dispatch, context management, sub-agent spawning, and sandboxing Design agent memory, context management, and tool-calling patterns Extend the MCP server with new tools and capabilities Enforce structured outputs and validation across LLM boundaries 2. LLM Quality, Evals & Observability Build the layer that lets ...