126 to 150 of 266 Model Context Protocol Jobs in London

React: the agents people talk to and the apps they click through, built in TypeScript. And you don't stop there. From API and MCP design to infrastructure on Vercel, AWS, Supabase, and BigQuery, plus the agents that work across the stack, you own complete features end to end, including ...

Developer Enablement, Enterprise Architecture, the AI Foundry, and engineering leadership to build the infrastructure that makes agentic development effective at FactSet specifically. This includes MCP servers and skills that give AI tools access to FactSet's standards, libraries, and institutional knowledge; verification and trust layers that catch hallucination and enforce ...

information is presented to a senior audience. Platform-level automation. Experience with low-code/no-code platforms (e.g. n8n, Copilot Studio), MCP, LLM observability tools (e.g. Langfuse), or managed model APIs (Azure AI Foundry, OpenAI, Anthropic).Modern development practices. Familiarity with any of: Docker, Terraform, CI/ ...

them reliably in production. Track record of building on shared enterprise data platforms (for example Snowflake) and delivering through modern interfaces such as MCP, rather than building parallel infrastructure. Team Building & People Leadership Proven ability to build, grow, and retain a high‐performing teams, defining roles, skills, and competencies … developing existing talent into a world‐class capability. Experience designing the operating model of a technical team, its ways of working, delivery cadence, quality standards, and tooling, in a product operating model context. A coaching leadership style that raises the technical bar while creating an environment where ...

other systems of record and engagement. Design integration patterns that let AI capabilities interoperate safely with enterprise data, identity,workflowand process automation platforms– including MCP and A2A and how these capabilities enable an enterprise Agent mesh. Understand the data,governanceand change implications of embedding AI into mission-critical enterprise processes. … Orchestration & control plane Architect the orchestration and control-plane layer that governs how AI capabilities are exposed,routedand managed across the enterprise. Design MCP, AI and LLM gateway layers for secure,observableand policy-controlled access to models and tools. Design agent and skills registries — including recommending suitable technologies and patterns ...

three pillars of the AI strategy; AI for Service Delivery, AI for Digital Products and AI for Productivity. This spans the JTC Agentic Platform (MCP-enabled orchestration and validation across JTC systems and market tools), the enterprise document extraction platform, end-to-end billing agents (Agentic Thames and the Agentic … systems and institutionalise the multi-platform Agent Builder for craft-your-own agents. Agentic Platform & AI ArchitectureOwn the engineering of the JTC Agentic Platform, MCP-enabled orchestration and validation across JTC systems and market tools, maintaining in-house control of the agentic layer to avoid LLM lock-in. Build around ...

architecture and delivery of multi-agent AI systems for high-value business use cases. defining engineering standards across orchestration architectures, context engineering, MCP integration, memory design, fine-tuning, evaluation frameworks and multimodal systems. building reusable AI capabilities including agent tools, MCP servers, skills and shared engineering assets. establishing quality … powered systems at enterprise scale. Expert-level Python engineering. Multi-agent architectures and orchestration frameworks. Context engineering, retrieval systems and memory architectures. MCP server and SKILL.md design and enterprise tooling integration. Model fine-tuning at scale (PEFT/(Q)LoRA). Building end-to-end voice AI pipelines ...

management, forecasting and optimisation (including usage‐based pricing shifts), and the staff access model. This includes: AI safety for internal use: sandboxing, policy, integrations, MCP governance, usage guardrails and monitoring expectations. The three platform pillars: control, monitoring and sandboxing (LLM and MCP gateway, anonymisation, local hardening, sandboxed cloud agent hosting … built or significantly scaled a team. Current, hands‐on fluency with the modern AI stack: frontier model platforms, agentic tooling and harnesses, MCP and integration patterns, evals, prompt and context engineering. AI security and governance: sandboxing, gateways (LLM, MCP, AI), DLP, guardrail enforcement and data‐boundary reasoning; able ...

agent approaches, and define evaluation, safety, and monitoring strategies for production use Own production deployment patterns including containerization, continuous integration and delivery, automated testing, model and prompt registries, model and version governance, monitoring and alerting, and rollback strategies Architect and deploy scalable, reliable, and secure machine learning … evaluation and safety patterns Familiarity with agentic building blocks and standards, including orchestration frameworks, context and memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit‐learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including ...

agent approaches, and define evaluation, safety, and monitoring strategies for production use Own production deployment patterns including containerization, continuous integration and delivery, automated testing, model and prompt registries, model and version governance, monitoring and alerting, and rollback strategies Architect and deploy scalable, reliable, and secure machine learning … evaluation and safety patterns Familiarity with agentic building blocks and standards, including orchestration frameworks, context and memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including ...

management, forecasting and optimisation (including usage-based pricing shifts), and the staff access model. This includes: AI safety for internal use : sandboxing, policy, integrations, MCP governance, usage guardrails and monitoring expectations. The three platform pillars : control, monitoring and sandboxing (LLM and MCP gateway, anonymisation, local hardening, sandboxed cloud agent hosting … built or significantly scaled a team. Current, hands-on fluency with the modern AI stack: frontier model platforms, agentic tooling and harnesses, MCP and integration patterns, evals, prompt and context engineering. AI security and governance: sandboxing, gateways (LLM, MCP, AI), DLP, guardrail enforcement and data-boundary reasoning; able ...

Engineering, Computer Science or equivalent; advanced degree preferred. Agentic AI/LLMs: LLM orchestration, prompt engineering, context‐window management and production guardrails; MCP, tool‐augmented agents and RAG at enterprise scale. Enterprise integration: Integrating AI into enterprise systems via APIs and data pipelines, with strong security, data governance ...

Engineering, Computer Science or equivalent; advanced degree preferred. Agentic AI/LLMs: LLM orchestration, prompt engineering, context-window management and production guardrails; MCP, tool-augmented agents and RAG at enterprise scale. Enterprise integration: Integrating AI into enterprise systems via APIs and data pipelines, with strong security, data governance ...

Solutions Architect to design end-to-end AI/LLM solutions for enterprise customers, leveraging Tencent Cloud TokenHub, foundation models, AI Agents, and MCP ecosystem. You will lead technical discovery workshops, architecture design sessions, POCs, validation, and production deployment planning, collaborating with customer engineering teams to deliver scalable, reliable ...

Senior Software Engineer to own the application and integration layer for a new generation of AI-powered products. The role spans backend, API design, MCP integration and frontend development with React and TypeScript. You will design scalable REST/GraphQL APIs, implement agent-to-agent connectivity, and build production-grade ...

Demonstrable AI engineering depth. You can show real systems where you made substantive decisions about agent harnesses, evals, hallucination containment, performance, agent sandboxing or MCP/tool design. Strong product engineering and technical judgment. You ship across interface, backend, data and deployment, reason from first principles and choose tools deliberately. ...

Will Be Doing Building real product features across Rebel end-to-end, with support and guidance from senior engineers Working with LLMs, agents, and MCP integrations from day one Learning by shipping: we believe the fastest way to grow is to have real ownership Contributing to our open-source ecosystem ...

including the component library, design tokens and documentation Extend the design system for AI-assisted development using Storybook and machine-readable interfaces such as MCP Design component APIs that resist misuse by AI and human developers Write high-quality, performant frontend code with React and TypeScript Partner with design, product ...

match you to the right one: Fluency with AI-assisted development, and interest in scaling agent-assisted workflows across the team (agentic CLI tools, MCP, skills, APIs) to amplify delivery. Familiarity with confidential computing technologies: TEEs, AMD SEV, Intel TDX, or Confidential Containers (CoCo). Experience building SaaS or PaaS ...

applications inside client systems, ensuring solutions meet enterprise requirements for performance, security, and reliability. Develop technical assets - Create reusable, production‐ready artefacts including MCP servers, sub‐agents, agent orchestration frameworks, and evaluation tooling that can be deployed across client workflows. Support enterprise deployments - Play a key technical role in rollouts … Identify patterns and scale - Recognise repeatable deployment patterns across engagements and contribute those insights back to Accenture's I&E FDE practice and our model provider partners to continuously improve our delivery playbook. Maintain cutting‐edge expertise - Stay ahead of the curve on LLM capabilities, agentic frameworks, evaluation methodologies ...

Associate Machine Learning Quality Engineer to join the Corporate Engineering AI team. You will help define evaluation frameworks and build automated test pipelines for MCP tools and Skills. You will collaborate with ML engineers to integrate evaluation hooks, address agentic risks, and provide testing evidence for PTB and PTO, ensuring ...

growth team at the forefront of AI transformation. You’ll build real product features across Rebel end-to-end, work with LLMs, agents, and MCP integrations, and grow through hands-on ownership from day one. We welcome diverse backgrounds and value curiosity, self-direction, and practical AI experience, with ...

cannot. You'll be early enough to shape how we sell. This role is based in London. We mainly use an in-person work model, with a flexible work-from-home policy. Take ownership of a named account list , guiding clients through the full sales cycle—from prospecting ...

Next.js Experience managing at least one cloud platform, such as Azure, AWS or GCP Experience working with AI development frameworks such as LangChain, foundation model platforms, vector databases, structured outputs, tracing and evaluation techniques Experience applying modern engineering practices, including testing, CI/CD, DevOps, observability, secure development, code … behaviour of AI‐enabled systems Strong communication skills to articulate complex technical solutions Ideally, you’ll also have Experience building complex systems, including writing MCP servers Experience with spec‐driven development and configuring coding‐agents Experience designing human‐in‐the‐loop workflows, including review, escalation and feedback mechanisms ...

every single requirement, please apply! You still may be a great fit for this role or other open roles. 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 … Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling) Experience operating production distributed systems on AWS/Azure, with a strong grasp of reliability, observability ...