51 to 58 of 58 MCP Jobs in England

AI and data-led innovation. Lead the full product lifecycle from ideation and proof of concept to launch and continuous optimisation. Partner with cross-functional teams to embed LLMs, MCP (Model Context Protocol), and autonomous AI agents into scalable enterprise products. Work closely with GTM and marketing teams to develop compelling positioning, messaging, and launch strategies. Define key metrics and …/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware intelligence. Expected Impact & Outcomes Launch of AI-powered features delivering measurable gains in efficiency, accuracy, and user … enterprise products. Strong understanding of data architecture, analytics, and governance. Experience integrating AI/ML models, LLMs, or agent-based systems into commercial products. Familiarity with Model Context Protocol (MCP) or similar AI orchestration frameworks. Ability to translate complex technology into clear business outcomes and ROI. Excellent communication, collaboration, and stakeholder management skills. Proficiency in Agile methodologies and tools (Jira More ❯

AI and data-led innovation. Lead the full product lifecycle from ideation and proof of concept to launch and continuous optimisation. Partner with cross-functional teams to embed LLMs, MCP (Model Context Protocol), and autonomous AI agents into scalable enterprise products. Work closely with GTM and marketing teams to develop compelling positioning, messaging, and launch strategies. Define key metrics and …/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware intelligence. Expected Impact & Outcomes Launch of AI-powered features delivering measurable gains in efficiency, accuracy, and user … enterprise products. Strong understanding of data architecture, analytics, and governance. Experience integrating AI/ML models, LLMs, or agent-based systems into commercial products. Familiarity with Model Context Protocol (MCP) or similar AI orchestration frameworks. Ability to translate complex technology into clear business outcomes and ROI. Excellent communication, collaboration, and stakeholder management skills. Proficiency in Agile methodologies and tools (Jira More ❯

AI and data-led innovation. Lead the full product lifecycle from ideation and proof of concept to launch and continuous optimisation. Partner with cross-functional teams to embed LLMs, MCP (Model Context Protocol), and autonomous AI agents into scalable enterprise products. Work closely with GTM and marketing teams to develop compelling positioning, messaging, and launch strategies. Define key metrics and …/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware intelligence. Expected Impact & Outcomes Launch of AI-powered features delivering measurable gains in efficiency, accuracy, and user … enterprise products. Strong understanding of data architecture, analytics, and governance. Experience integrating AI/ML models, LLMs, or agent-based systems into commercial products. Familiarity with Model Context Protocol (MCP) or similar AI orchestration frameworks. Ability to translate complex technology into clear business outcomes and ROI. Excellent communication, collaboration, and stakeholder management skills. Proficiency in Agile methodologies and tools (Jira More ❯

repos, case studies, or live services). Desired Node.js alongside Python for services or integrations. Experience with vector databases (e.g., Chroma) and embedding pipelines. LangChain or CrewAI for orchestration; MCP servers for integrations. Security hygiene (secrets, permissions, least-privilege) and practical data-privacy basics. Planning & execution in Linear (or similar). Tools & Stack Backend/Runtime: Python (FastAPI), Node.js. Datastores … . Vectors/Embeddings: Chroma (or similar). AI Models & APIs: Claude (Anthropic), Gemini (Google); Amazon Nova Canvas (vision), Deepgram (audio). AI Dev Tools: LangChain or CrewAI (orchestration), MCP servers (integration), GitHub Copilot/Claude Code. Infrastructure: AWS (serverless functions), Docker (primarily for custom MCPs). Frontend (when needed): React/Next.js (for dashboards/admins, used selectively). More ❯

repos, case studies, or live services). Desired Node.js alongside Python for services or integrations. Experience with vector databases (e.g., Chroma) and embedding pipelines. LangChain or CrewAI for orchestration; MCP servers for integrations. Security hygiene (secrets, permissions, least-privilege) and practical data-privacy basics. Planning & execution in Linear (or similar). Tools & Stack Backend/Runtime: Python (FastAPI), Node.js. Datastores … . Vectors/Embeddings: Chroma (or similar). AI Models & APIs: Claude (Anthropic), Gemini (Google); Amazon Nova Canvas (vision), Deepgram (audio). AI Dev Tools: LangChain or CrewAI (orchestration), MCP servers (integration), GitHub Copilot/Claude Code. Infrastructure: AWS (serverless functions), Docker (primarily for custom MCPs). Frontend (when needed): React/Next.js (for dashboards/admins, used selectively). More ❯

repos, case studies, or live services). Desired Node.js alongside Python for services or integrations. Experience with vector databases (e.g., Chroma) and embedding pipelines. LangChain or CrewAI for orchestration; MCP servers for integrations. Security hygiene (secrets, permissions, least-privilege) and practical data-privacy basics. Planning & execution in Linear (or similar). Tools & Stack Backend/Runtime: Python (FastAPI), Node.js. Datastores … . Vectors/Embeddings: Chroma (or similar). AI Models & APIs: Claude (Anthropic), Gemini (Google); Amazon Nova Canvas (vision), Deepgram (audio). AI Dev Tools: LangChain or CrewAI (orchestration), MCP servers (integration), GitHub Copilot/Claude Code. Infrastructure: AWS (serverless functions), Docker (primarily for custom MCPs). Frontend (when needed): React/Next.js (for dashboards/admins, used selectively). More ❯

repos, case studies, or live services). Desired Node.js alongside Python for services or integrations. Experience with vector databases (e.g., Chroma) and embedding pipelines. LangChain or CrewAI for orchestration; MCP servers for integrations. Security hygiene (secrets, permissions, least-privilege) and practical data-privacy basics. Planning & execution in Linear (or similar). Tools & Stack Backend/Runtime: Python (FastAPI), Node.js. Datastores … . Vectors/Embeddings: Chroma (or similar). AI Models & APIs: Claude (Anthropic), Gemini (Google); Amazon Nova Canvas (vision), Deepgram (audio). AI Dev Tools: LangChain or CrewAI (orchestration), MCP servers (integration), GitHub Copilot/Claude Code. Infrastructure: AWS (serverless functions), Docker (primarily for custom MCPs). Frontend (when needed): React/Next.js (for dashboards/admins, used selectively). More ❯

repos, case studies, or live services). Desired Node.js alongside Python for services or integrations. Experience with vector databases (e.g., Chroma) and embedding pipelines. LangChain or CrewAI for orchestration; MCP servers for integrations. Security hygiene (secrets, permissions, least-privilege) and practical data-privacy basics. Planning & execution in Linear (or similar). Tools & Stack Backend/Runtime: Python (FastAPI), Node.js. Datastores … . Vectors/Embeddings: Chroma (or similar). AI Models & APIs: Claude (Anthropic), Gemini (Google); Amazon Nova Canvas (vision), Deepgram (audio). AI Dev Tools: LangChain or CrewAI (orchestration), MCP servers (integration), GitHub Copilot/Claude Code. Infrastructure: AWS (serverless functions), Docker (primarily for custom MCPs). Frontend (when needed): React/Next.js (for dashboards/admins, used selectively). More ❯