1 to 25 of 172 Remote/Hybrid Permanent Model Context Protocol Jobs

Copilot, Microsoft 365 services, business applications, content repositories, and line of business systems.Applying emerging interoperability frameworks such as Model Context Protocol (MCP) and Agent to Agent (A2A) patterns, where appropriate, to enable secure interaction between agents, enterprise knowledge, business applications, and workplace services.Supporting the adoption of modern … integrating enterprise systems through APIs, Microsoft Graph, custom connectors, and modern integration approaches.Understanding of emerging standards such as Model Context Protocol (MCP) and Agent to Agent (A2A) interoperability concepts and their application within enterprise environments.Knowledge of enterprise security, identity, compliance, information management, and governance principles within Microsoft ...

Generative AI and Agentic AI using Google ADK . Design, develop and test AI Agents and work with Model Context Protocol (MCP) and MCP servers. Write high-quality code in Python and/or Java , working across modern AI and platform technologies. Provide technical leadership, mentoring … highly desirable. Experience with Generative AI and AI Agents , ideally including Google ADK . Practical experience with Model Context Protocol (MCP) and AI/data/service integration is highly desirable. Strong understanding of REST APIs, networking, databases and CLI tooling , with Postgres/Oracle experience preferred. ...

demonstrate the power of Zendesk headless technology and help customers embed Zendesk deep into their workflows inside and outside of the core platform via MCP and A2A technology. AI & Platform Architecture Autonomous Service Deployment: Master and deploy the Zendesk Agent Builder and Action Builder to architect multi-step, agentic workflows … target. Ecosystem Integration & Connectivity: Architect modern integrations connecting the Zendesk platform to external AI platforms and enterprise applications. Design these connections utilizing the Zendesk MCP (Model Context Protocol) Server, comprehensive APIs, and advanced Integration Platforms as a Service (iPaaS), while applying scalable enterprise integration patterns. Knowledge & Memory ...

designing scalable, secure, and responsible AI solutions that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Agentic Frameworks, Knowledge Graphs, Semantic Layers, Vector Databases, and Cloud AI services.This role will act as the bridge between Business, Product, Engineering, Data, Security, Risk … Generation (RAG) solutions for enterprise knowledge retrieval.Design Agentic AI and multi-agent frameworks to automate complex business processes.Implement Model Context Protocol (MCP) patterns for tool and system integration.Define standards for:Prompt EngineeringContext ManagementAI EvaluationGrounding & RetrievalHallucination ReductionAI ObservabilityLead architecture of AI assistants, copilots, virtual agents, and autonomous workflows.Your ...

Business (LOB) squads. The overall objective of this role is to build production‐grade agent reasoning loops, custom Model Context Protocol (MCP) servers and robust error‐handling mechanisms that adhere to enterprise safety and quality standards. Working closely with fellow engineers and business stakeholders, you’ll help … Writes robust, production‐quality agent reasoning logic, memory management and sub‐agent delegation workflows in Python. Develops custom Model Context Protocol (MCP) servers connecting AI agents to enterprise systems (ServiceNow, JIRA, DBaaS, Kafka, internal REST/gRPC services). Implements resilient error handling, automated retry mechanisms, fallback ...

intelligent AI agents, copilots, and automation solutions using Anthropic Claude, large language models (LLMs), retrieval-augmented generation (RAG), Model Context Protocol (MCP), and agent orchestration frameworks. Experience developing multi-agent workflows, integrating AI solutions with enterprise systems, and taking solutions from proof of concept to production … deploying agentic AI solutions using platforms such as Anthropic Claude, including AI agents, tool orchestration, reasoning workflows, Model Context Protocol (MCP), and enterprise-scale automation use cases. Hands‐on experience building AI-enabled systems, such as LLM pipelines, document extraction, structured output generation, AI-assisted analytics, prediction ...

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 ...

tools, retrieval systems and configurations for production use. Integrate AI systems with enterprise APIs, databases, applications and data platforms. Develop reusable connectors, APIs and Model Context Protocol tools. Build automated CI/CD, testing, configuration management and deployment workflows. Implement authentication, access control, secrets management, security … with Azure, AWS or Google Cloud, Kubernetes, Helm, Terraform and CI/CD technologies. Experience with LangGraph, AutoGen, smolagents or similar frameworks. Experience with Model Context Protocol, model‐serving platforms, vector databases and LLM gateways. Experience implementing AI evaluation, observability, tracing and performance monitoring. Experience with ...

enablement capabilities that support the adoption of Generative AI and agentic workflows across the organisation. Own the roadmap, strategy, and engineering delivery of the MCP ecosystem, enabling secure integration between AI assistants, enterprise systems, data sources and business applications. Lead the design, development, deployment and operational support of AI agents … solutions that drive measurable business outcomes. Desirable Experience Experience building or operating AI Agents, AI Assistants, Copilots or AI Enablement Platforms. Experience with MCP (Model Context Protocol), MCP Servers, MCP Clients or enterprise AI integration frameworks. Knowledge of LLMOps, AI evaluation frameworks, model routing ...

optimize prompts and interaction strategies for LLMs to achieve desired outcomes in agentic systems. Integrate various tools, APIs, and data sources, potentially utilizing MCP Servers, to enhance model context and tool integration. Develop robust, scalable, and maintainable code in Python for all components of the agentic applications, from … translate requirements into technical solutions. Stay up-to-date with the latest research and developments in generative AI, LLMs, agentic systems, and protocols like MCP, evaluating their potential for our products. Contribute to the architecture and technical roadmap of our AI initiatives. Mentor junior engineers and share knowledge within ...

optimize prompts and interaction strategies for LLMs to achieve desired outcomes in agentic systems. Integrate various tools, APIs, and data sources, potentially utilizing MCP Servers, to enhance model context and tool integration. Develop robust, scalable, and maintainable code in Python for all components of the agentic applications, from … translate requirements into technical solutions. Stay up-to-date with the latest research and developments in generative AI, LLMs, agentic systems, and protocols like MCP, evaluating their potential for our products. Contribute to the architecture and technical roadmap of our AI initiatives. Mentor junior engineers and share knowledge within ...

automated testing, regression testing,hallucination detection and response quality monitoring. Develop multi-agent workflowsand integrate enterprise systems using Model Context Protocol (MCP) andagent-to-agent (A2A) communication. Monitor production AIsolutions, incorporating user feedback to improve model performance,retrieval accuracy and reliability. Deploy and manage AI/… Graph RAG, knowledge graphs andadvanced retrieval architectures . Knowledge of agent memoryframeworks, including episodic and semantic memory. Hands-on experience with ModelContext Protocol (MCP) and Agent-to-Agent (A2A) frameworks. Experience with LLM evaluationtechniques, LLM-as-a-judge, groundedness testing and hallucinationdetection. Familiarity with Snowflake,Kubernetes, Splunk, Confluence ...

graph, and hybrid approaches. Design multi-agent systems with modern orchestration and reasoning architectures, including human-in-the-loop and autonomous frameworks. Define memory, context, planning, tool-use, and reasoning strategies for agentic systems. Stay technical. Contribute to architecture, critical-path code, design reviews, and the hardest technical problems. … Semantic Kernel, Strands. Advanced retrieval : Graph RAG, knowledge graphs, context graphs, hybrid search, vector databases. Agentic patterns : multi-agent architectures, planning and reasoning, MCP (Model Context Protocol). Model customization: fine-tuning, distillation, and model evaluation at scale. What success looks like in this ...

advanced capabilities in generative AI, agentic workflows, secure enterprise knowledge experiences, and AI-enabled automation. Our teams apply Anthropic-aligned practices in prompt and context engineering, retrieval-augmented generation (RAG), tool use, structured outputs, model evaluation, safety, governance, and human-in-the-loop controls. As an early-career … IntegrationHub, or Flow Designer. Exposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud. Familiarity with Model Context Protocol (MCP) concepts, secure API integration patterns, or connecting AI applications to enterprise tools and data sources. Experience working in an agile software‐development environment. Interest ...

Design, develop and maintainAI-powered applications, intelligent agents and copilot solutions usingPython. Build and integrate APIs, agenttools and Model Context Protocol (MCP) servers to connect AI applicationswith enterprise systems. Develop retrieval-augmentedgeneration (RAG) pipelines, including document ingestion, embeddings,indexing and retrieval. Build and maintain dataprocessing pipelines using … practices and responsible AI principles. Nice to Have Experience with AWS cloudservices. Hands-on experience withDatabricks and MLOps frameworks. Knowledge of Model ContextProtocol (MCP) and AI agent orchestration. Experience with AI evaluationframeworks, LLM-as-a-judge techniques and automated regression testing. Familiarity with OpenTelemetry,observability and distributed tracing. Experience ...

enterprise customers. It is a React and TypeScript single-page application, and almost everything on its screen arrives as a stream from a language-model agent. What you will do: Build an interface that people can trust while the content on it is still arriving, changing and occasionally wrong. … language model in production: streaming, partial output, retries, and showing uncertainty. Hands-on knowledge of the Model Context Protocol (MCP) and MCP Apps, AG-UI or A2UI. Experience building with Lit and Web Components, including shadow DOM and custom elements used from other frameworks. Expression languages ...

Engineer at Oxford Dynamics, you will build and ship agentic AI systems in production: designing the multi-agent pipelines, the reasoning and retrieval, the model integration, and the infrastructure that carries them into production. These are systems people rely on to make consequential decisions, so what you build … behaviour, performance monitoring) Experience with agent orchestration patterns and inter‐agent communication protocols (e.g. A2A) Familiarity with the Model Context Protocol (MCP) for tool and context integration in agentic systems Familiarity with secure‐by‐design development principles (ISO 27001, NIST, OWASP) Experience in defence, national security ...

Engineer at Oxford Dynamics, you will build and ship agentic AI systems in production: designing the multi-agent pipelines, the reasoning and retrieval, the model integration, and the infrastructure that carries them into production. These are systems people rely on to make consequential decisions, so what you build … behaviour, performance monitoring) Experience with agent orchestration patterns and inter‐agent communication protocols (e.g. A2A) Familiarity with the Model Context Protocol (MCP) for tool and context integration in agentic systems Familiarity with secure‐by‐design development principles (ISO 27001, NIST, OWASP) Experience in defence, national security ...

Engineer at Oxford Dynamics, you will build and ship agentic AI systems in production: designing the multi-agent pipelines, the reasoning and retrieval, the model integration, and the infrastructure that carries them into production. These are systems people rely on to make consequential decisions, so what you build … behaviour, performance monitoring) Experience with agent orchestration patterns and inter-agent communication protocols (e.g. A2A) Familiarity with the Model Context Protocol (MCP) for tool and context integration in agentic systems Familiarity with secure‐by‐design development principles (ISO 27001, NIST, OWASP) Experience in defence, national security ...

deliver scalable AI solutions, including Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, and intelligent automation capabilities aligned to business objectives.* Evaluate technology, model, and platform options, providing recommendations based on business value, cost, risk, strategic alignment, scalability, and long-term supportability.* Follow Systems Development Lifecycle (SDLC) and governance … Observability Frameworks* LLM Fine-tuning and Adaptation Techniques* Hands-on experience with Azure AI Foundry, Azure OpenAI Service, Model Context Protocol (MCP), and modern AI orchestration frameworks.* Strong programming skills in Python, with experience developing scalable APIs, AI services, and automation solutions.* Experience implementing vector search solutions ...

technologies including Google Gemini, Open-Source Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agent Development Kits (ADK), Model Context Protocol (MCP), and Google Cloud Platform (GCP). The role provides exposure to cloud-native architecture, MLOps, AI governance, and enterprise-scale solution delivery, enabling … ecosystems. Advanced Python development skills with experience building enterprise-grade applications. Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures. Strong understanding of ADK, MCP, AI orchestration frameworks, and integration patterns. Experience developing REST APIs, microservices, and distributed applications. Hands-on experience with Google Cloud Platform (GCP) services and cloud ...

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 ...

response through to root cause and a closed corrective action. Operate the agent runtime layer. Route production agents through the enterprise AI Gateway and MCP Gateway rather than direct model and tool access, migrate existing agents onto that governed path, and keep tool surfaces scoped, versioned and least-privilege … management, rate limiting and budget enforcement. Working knowledge of tool-calling architecture for agents, including the Model Context Protocol: what an MCP server is, how tools are scoped and authorized, and why tool access is brokered through a gateway rather than granted directly. Experience with containerization ...

Amazon Bedrock; model gateways and routing, retrieval and hybrid search, document ingestion, tool/function calling, Model Context Protocol (MCP), and agent orchestration AI Evaluation & Quality: Eval harnesses and golden datasets, LLM-as-judge and human-in-the-loop review, regression suites, and red-teaming Observability … support to developers using platform services, triaging and resolving requests and issues. Support governed self‐service access to AI platform capabilities, including model access, retrieval tooling, and evaluation workflows, so AI capabilities can move from prototype to production using standard platform patterns. CI/CD, Release Management & Test Automation ...

culture that values craft, ownership, and continuous learning. Responsibilities Implement software components and applications for AI systems, with a primary focus on MCP (Model Context Protocol) tools and AI agent frameworks Operate as a committed member of a skilled SCRUM team — take ownership of your work, ship … within a leading financial institution Operate in a culture that actively encourages and sponsors personal and professional development Build with cutting‐edge AI tools — MCP, LLMs, agent frameworks — at real enterprise scale Flexible hybrid working model supporting both office collaboration and remote productivity What we’ll provide ...