26 to 50 of 135 Model Context Protocol Jobs in England

where ceremony adds cost without value. The role engages the Chief Architect early, pushes back constructively when platform standards do not fit the ECS context, and helps teams close decisions with conviction rather than endless review. Reason About Cost and Unit EconomicsInfrastructure choices are sized, cost trajectories modelled … signal back into product and architecture decisions Bonus Points Background in email security, threat detection, DLP, identity, or data platforms Familiarity with agentic AI, MCP (Model Context Protocol), or LLM application architecture Experience with eval design for AI features, product discovery practices, or data contract/data ...

architecting AI solutions within complex infrastructures, ensuring data sovereignty and secure governance. Experience in designing intuitive interfaces for complex AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust. Ability to design end‐to‐end secure, observable multi‐agent systems using complex design patterns (ReAct … expertise, systems engineering, and coding skills to build an engineering squad. Identify skill gaps in emerging tech (Model Context Protocol (MCP), tool‐calling, and foundation models), ensuring the team maintains subject matter expertise in an evolving AI stack. Collaborate with product and engineering to resolve blockers ...

Conversational AI and CX applications, transitioning from rapid prototypes to production‐grade agentic workflows (e.g., multi‐agent systems, Model Context Protocol (MCP) servers) that drive measurable return on investment. Architect and code conversational flows that are not just functional, but optimized for the "connective tissue" between ...

Conversational AI and CX applications, transitioning from rapid prototypes to production‐grade agentic workflows (e.g., multi‐agent systems, Model Context Protocol (MCP) servers) that drive measurable return on investment. Architect and code conversational flows that are not just functional, but optimized for the "connective tissue" between Google ...

Python, APIs, etc. Familiarity with AI-assisted development and agentic coding tools (Claude Code, Cursor, Codex) and the Model Context Protocol (MCP) is a plus Experience with web development and containerized software is a plus Strong sales acumen and proven experience partnering with AEs to drive ...

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. ...

approval gates so developers can verify and correct agent output before it is merged. Integrate tools and data sources into the agents via MCP (Model Context Protocol). Set up evaluation, guardrails and tests to catch incorrect output early. Work alongside engineering team's and upskill them ...

Azure OpenAI Design, develop and support secure REST APIs using C# and .NET Build and manage Azure Functions and serverless services Develop and support MCP Servers and AI integration services Design event-driven architectures using Azure Service Bus Manage APIs through Azure API Management Expose AI capabilities through secure, auditable … design and development Azure AI Foundry Azure OpenAI Event-driven architecture Azure integration engineering Secure API design Production support and operational ownership Desirable Experience MCP Servers Model Context Protocol Semantic Kernel Prompt Flow Agentic AI AI orchestration frameworks Copilot Studio Power Platform integrations RAG architectures AI governance ...

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 … structure and scale growth opportunities through partnerships, platform ecosystems and go-to-market frameworks Deep understanding of the AI platform landscape, including large language model infrastructure, agentic frameworks and data standards such as Model Context Protocol, with the ability to translate capabilities into product use cases ...

engineering teams on technical dependencies and integration requirements. Represent RME customer needs in architectural decisions for AI‐assisted triage, agentic AI (MCP protocol), alarm consolidation, and mobile‐first design. Manage stakeholder alignment across RME field leadership, GES, ELM, Controls Engineering, and executive steering committees. About the team: The Controls … engineering, and AI/ML – building real‐time web applications, data pipelines (Kinesis, COSMOS), spatial intelligence platforms (Spectralink), and agentic AI systems (Graph RAG, MCP protocol). This is a high‐impact team with outsized influence on Amazon’s operational efficiency across the fulfillment network. This role is based ...

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 ...

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 ...

sharing infrastructure, governance, comms, and the firm‐wide adoption dashboard. Your primary toolkit today spans the modern AI engineering stack – coding agents, agentic harnesses, MCP, in‐platform AI in Snowflake and Databricks, and the JHOS/NEXUS platform Percepta is building – but the firm’s AI strategy is platform‐agnostic. … Foundry, APIM, Cortex, Databricks Genie Code, and the forthcoming LLM Gateway Stay current with the rapidly evolving AI engineering landscape – coding agents, agentic harnesses, MCP, model releases, benchmarks, DORA and industry research – and translate what matters into practical curriculum changes Collaborate with Technology, Security, and Responsible AI teams ...

sharing infrastructure, governance, comms, and the firm‐wide adoption dashboard. Your primary toolkit today spans the modern AI engineering stack — coding agents, agentic harnesses, MCP, in‐platform AI in Snowflake and Databricks, and the JHOS/NEXUS platform Percepta is building — but the firm’s AI strategy is platform‐agnostic. … Foundry, APIM, Cortex, Databricks Genie Code, and the forthcoming LLM Gateway Stay current with the rapidly evolving AI engineering landscape — coding agents, agentic harnesses, MCP, model releases, benchmarks, DORA and industry research — and translate what matters into practical curriculum changes Collaborate with Technology, Security, and Responsible AI teams ...

/ML pipelines from data preparation through to production. Working with technical and business stakeholders to deliver AI solutions. Desirable experience includes MLflow, MCP, Docker, Kubernetes, GitLab CI/CD and Azure Data Factory. What's on offer Up to 82,000 salary Annual performance bonus 28 days' holiday plus ...

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 ...

aligned with engineering standards. Comfortable working across technical implementation, team enablement, stakeholder communication, and operational rollout. Curious about areas such as AI agents, MCP, RAG, evals, prompt/workflow design, AI observability, and developer productivity measurement. The Impact You Will Have Help engineering teams adopt AI in a way that ...

their impact. We value your AI skills if you have built fluency across the agentic engineering toolchain — coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks — and can describe projects where you shipped real work with these tools. You know how to drive an agent ...

gateway/Bedrock patterns, data residency, SSO/OIDC federation, and cost controls. Experience with Claude/Anthropic, OpenAI, Microsoft Copilot families, including MCP, connectors, skills, and trade‐offs. Strong understanding of AI testing disciplines (accuracy, hallucination, bias, prompt evaluations) and AI governance/risk (DPIA, data classification, FCA considerations ...

gateway/Bedrock patterns, data residency, SSO/OIDC federation, and cost controls. Experience with Claude/Anthropic, OpenAI, Microsoft Copilot families, including MCP, connectors, skills, and trade-offs. Strong understanding of AI testing disciplines (accuracy, hallucination, bias, prompt evaluations) and AI governance/risk (DPIA, data classification, FCA considerations ...

Kubernetes, CI/CD, and major cloud platforms. Expertise in LLMs, prompt engineering, vector DBs, RAG pipelines, and Agentic orchestration frameworks. Agentic/integrations: MCP, Salesforce/SAP/Other. Excellent communication with both technical and executive stakeholders. Mentorship capability and collaborative team‐first mindset. BS/MS/ ...

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 ...

vendor. Experience shipping software via marketplaces (Atlassian Marketplace, monday.com Apps, and similar). Hands‐on with agentic development tooling beyond chat (Claude Code, Cursor, MCP‐based workflows, and the like). Experience taking AI features to production at scale: evaluation, cost control, latency, safety. Why us? Backed by 20+ years ...

data grounding Architect reusable AI design patterns including human‐in‐the‐loop workflows and multi‐agent coordination models Apply agent integration and communication standards (MCP, A2A, OpenAPI, REST, gRPC) Lead technical delivery of AI projects, managing timelines, dependencies, and stakeholder expectations Ensure delivery adheres to AI governance, data privacy … model evaluation approaches Hands‐on experience with multi‐agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel) Familiarity with orchestration protocols such as MCP, A2A, and OpenAPI‐based integration Strong Python development skills and knowledge of CI/CD, DevOps, and cloud‐native architectures Practical experience with Azure (Azure OpenAI ...

/CD, build systems, artifact repositories, cloud‐native technologies, or software supply chain security; Hands‐on experience with AI Agents, RAG, tool use, MCP/Skills, AI evaluation, or AI observability; Experience with large‐scale distributed systems, globally distributed multi‐region systems, or infrastructure for AI training and inference ...