21 of 21 Model Context Protocol Jobs in the North of England

frontend and backend services—from designing highly performant, intuitive modern user interfaces to building robust API services, Model Context Protocol (MCP) services, and autonomous AI agents. In this role, you will lead the architecture, design, and deployment of scalable Generative AI solutions, ensuring seamless integration into … both frontend and backend development, combined with hands-on experience building production-ready GenAI features. You will bridge the gap between backend APIs, custom MCP services, agentic workflows, and responsive modern user interfaces to deliver intelligent, automated planning experiences for our global customers. Your ImpactTechnical Leadership & System Architecture: Architect, design ...

supporting a public sector organisation with the secure rollout and governance of AI-enabled developer tooling, including GitHub Copilot, Copilot CLI, GitHub CLI and MCP (Model Context Protocol) servers. This role would suit a Platform Engineer, DevSecOps Engineer, AI Platform Engineer, Developer Experience Engineer or GitHub Enterprise … Administrator with experience balancing innovation, security and governance. Key Responsibilities Administer and configure GitHub Enterprise, GitHub Copilot and Copilot CLI. Evaluate, test and govern MCP servers, including GitHub, Jira and Confluence integrations. Implement AI security controls, access policies and approval processes. Conduct threat modelling and AI risk assessments in partnership ...

Generative AI workloads run on: the platform layer beneath LLMs, agents, and MLOps pipelines. This spans GPU-accelerated compute and container platforms, model serving and gateway infrastructure, evaluation and guardrail systems, and the MLOps/LLMOps tooling that takes a model from experiment to production. You’ll work … workload cost attribution • Agent orchestration and tool-calling frameworks (e.g. LangGraph or equivalent), including familiarity with the Model Context Protocol (MCP) • Evaluation engineering (golden datasets, regression gates in CI, LLM-judge calibration) • Guardrail and AI-observability tooling (e.g. NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust) MLOps & LLMOps ...

enabled automation Prompt engineering, AI evaluation and Responsible AI AI orchestration frameworks e.g. LangChain, Semantic Kernel, Model Context Protocol (MCP) Data engineering, pipelines, modelling and governance Advanced analytics, machine learning and statistical modelling Data visualisation and insight solutions Candidates should understand the importance of trusted, accessible ...

production-ready development. A practical, hands-on approach to AI experimentation and AI-assisted coding. Desirable Experience Model Context Protocol ( MCP ) and AI agents. AWS, particularly Lambda, SQS/SNS, Bedrock or S3. Vector databases, embeddings and retrieval-augmented generation (RAG). Prompt engineering and LLM evaluation. ...

Excellence under a unified, high-standard operating model. Direct the rollout of agentic analytics, using Claude and Model Context Protocol (MCP) to enable self-serve access to certified data. Collaborate with Analytics Engineering to shape the unified semantic layer migration onto dbt MetricFlow. Establish evaluation frameworks, telemetry … product management experience, preferably with partner- or customer-facing data products. Practical understanding of agentic data access concepts, including plugins, skills, and MCP architectures. Solid technical foundation in SQL, modern data warehousing (BigQuery, dbt), and semantic layer BI tools such as Looker. Demonstrated ability to translate analytics deliverables into commercial ...

embedding AI-augmented development workflows across the team, driving measurable gains in velocity, quality, and innovationLeverage AI coding assistants (Windsurf, Claude Code) and Model Context Protocols (MCPs) to accelerate software delivery, automate repetitive tasks, and elevate engineering standardsDesign, build, and deploy intelligent, scalable solutions that integrate machine learning … driven engineering practices, fostering a culture of continuous learning and experimentationPartner with Architecture and Data Science teams to define best practices for ML model deployment, data pipeline design, and cloud infrastructure standardsConduct thorough code reviews with a focus on AI-assisted quality, providing constructive feedback to enhance code quality ...

fully defined spec. Engineering standards: Raise the quality of the team through code review, mentorship, and unblocking teammates. You will communicate clearly, share context, and help others grow while keeping delivery moving. Who You AreBeyond the qualifications, we hire through a specific lens. These aren't buzzwords; they … designing or running experiments, including A/B tests or betas, to validate product decisions. Experience with browser DOM inspection or automation. Familiarity with Model Context Protocol or building tools for LLM agents. Familiarity with real-time data pipelines or streaming architectures. Accessibility experience. Passion for continuous ...

SKILLS AI Engineer, Agentic AI, Generative AI, LLM, Large Language Models, Python, SQL, RAG, Prompt Engineering, Azure, APIs, AI Agents, LangChain, LangGraph, Claude, MCP, AI Automation ...

RBAC and Cost Controls. Software Engineering: Clean Code (SOLID, DRY), DDD, modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens. Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK. WHAT YOU'LL LOVE ...

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

document processing and retrieval-based solutions. Logic Apps, API Management, Service Bus and Key Vault. TypeScript, JavaScript or Python. Docker, infrastructure as code or Model Context Protocol. Salary & benefits £70,000–£75,000 salary. Four days working from home- one office Flexible working hours. Competitive pension scheme. Health ...

estates to lakehouse or metadata-driven architectures. Customer Data Platforms or event-driven systems. Data-quality tools such as dbt tests or Great Expectations. MCP servers or governed natural-language data interfaces. Financial crime, fraud or regulatory-reporting data. Power BI administration and semantic modelling. Why apply? This ...

Skills & Experience 4+ years in Product Management experience - in fast-paced and agile environments. Proven track record of shipping B2B SaaS or enterprise software; MCP and headless experience is a strong plus. Comfortable owning a technical product - able to hold your own with engineers on architecture, performance and trade ...

estates to lakehouse or metadata-driven architectures. Customer Data Platforms or event-driven systems. Data-quality tools such as dbt tests or Great Expectations. MCP servers or governed natural-language data interfaces. Financial crime, fraud or regulatory-reporting data. Power BI administration and semantic modelling. The opportunity This ...

Doing Contributing to the development of our internal AI platform Building AI-powered client solutions: RAG pipelines, agent architectures, LLM integrations, protocol-driven tooling Helping design internal AI tooling to accelerate delivery Supporting our upskilling programme with technical AI knowledge-sharing Keeping across emerging AI tools, frameworks and protocols … projects, not just professional work (API integrations, prompt engineering, agent workflows, RAG systems) Proficiency in 2+ modern programming languages Awareness of evolving AI tooling (MCP, A2A, or similar) Some consultancy or client-facing experience, or a strong interest in moving into it Desirable: Vector databases, embeddings, fine-tuning Cloud experience ...

Doing Contributing to the development of our internal AI platform Building AI-powered client solutions: RAG pipelines, agent architectures, LLM integrations, protocol-driven tooling Helping design internal AI tooling to accelerate delivery Supporting our upskilling programme with technical AI knowledge-sharing Keeping across emerging AI tools, frameworks and protocols … projects, not just professional work (API integrations, prompt engineering, agent workflows, RAG systems) Proficiency in 2+ modern programming languages Awareness of evolving AI tooling (MCP, A2A, or similar) Some consultancy or client-facing experience, or a strong interest in moving into it Desirable: Vector databases, embeddings, fine-tuning Cloud experience ...

Doing Contributing to the development of our internal AI platform Building AI-powered client solutions: RAG pipelines, agent architectures, LLM integrations, protocol-driven tooling Helping design internal AI tooling to accelerate delivery Supporting our upskilling programme with technical AI knowledge-sharing Keeping across emerging AI tools, frameworks and protocols … projects, not just professional work (API integrations, prompt engineering, agent workflows, RAG systems) Proficiency in 2+ modern programming languages Awareness of evolving AI tooling (MCP, A2A, or similar) Some consultancy or client-facing experience, or a strong interest in moving into it Desirable: Vector databases, embeddings, fine-tuning Cloud experience ...

feedback to improve the Factory. • Work with partner and developer teams to enable appropriate external use of capabilities through secure APIs and tools, including MCP, where this supports the strategy. Own delivery and the economics of AI • Translate strategy into a prioritised roadmap with clear customer outcomes, milestones, dependencies … limitations. Additional experience that would be valuable • Building agent frameworks, workflow orchestration, AI evaluation or observability capabilities, or developer platforms for AI. • Working with MCP, secure tool access, agent interoperability or external developer and partner ecosystems. • Delivering products where sensitive data, financial accuracy, permissions and auditability are central to customer ...

Generative AI and Agentic AI, including their capabilities, limitations and failure modes, with sound judgement on when deterministic software is the better solutionExperience with context engineering, including retrieval-augmented generation (RAG), grounding, knowledge sources, memory, prompt design … controlled access to information. Experience building AI agents and agentic workflows, including task decomposition, orchestration, state management, tool integration through protocols such as MCP and human approval controls. Experience using AI-assisted development tools and coding agents as a core part of how you engineer, applying strong verification and taking ...

Enterprise AI stack: HANA Cloud graph and vector store sizing, CAP service layer design, BTP subaccount structure, and Claude model route governance via MCP connector and Skald Gateway. Proven ability to design and govern GraphRAG knowledge planes: ontology and graph edge construction, domain and provenance tagging strategy, trust gate … complete deployment lifecycle — from subaccount provisioning and ingestion pipeline build through to client handover and production go-live. Direct experience with Claude Code, MCP-based tool integrations, or equivalent agentic AI frameworks in a controlled enterprise environment, including connector setup, security approval, and end-to-end testing. Experience with ...