51 to 75 of 583 Permanent Model Context Protocol Jobs

with clarity, speed, and confidence. If you are excited about this opportunity but do not meet every single requirement, 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 … issue resolution and feedback collection Preferred: Familiarity with financial data, company information, credit research, corporate ownership or risk management solutions Preferred: Experience working with Model Context Protocol services, agentic workflows, generative artificial intelligence platforms or embedded data solutions Preferred: Familiarity with basic coding and analytics principles, including ...

helping organisations move from AI experimentation to secure, governed, and production-ready agentic architectures. The role spans Agentic Architecture, Agent Control Planes, AI Gateways, MCP/A2A, Agentic Security & Governance, Observability and Agentic Quality Engineering, alongside enterprise integration and API architecture. As Agentic AI is an emerging field … systems o Agent orchestration and Control Planes o AI/model gateways and model routing o Model Context Protocol (MCP) and Agent-to-Agent (A2A) o Agent/tool discovery and registries o Agent identity and delegated identity o Human-in-the-loop controls ...

Claude on Bedrock, Gemini, Azure OpenAI), selected per use case for quality, latency and cost. Interfaces: Tools and Model Context Protocol (MCP) for integration; standards-based APIs and secure auth for client systems. What you'll do Conceptualize fast: embed with stakeholders, frame a business process … serve. Engineer the agent core: apply prompt engineering, context engineering, prompt caching, RAG/context-graph retrieval, memory, tool/function calling, MCP integration and multi-agent orchestration. Integrate to standards: connect agents into client ecosystems through proven integration patterns, standards-based APIs and secure authentication. Make reusability ...

Claude on Bedrock, Gemini, Azure OpenAI), selected per use case for quality, latency and cost. Interfaces: Tools and Model Context Protocol (MCP) for integration; standards-based APIs and secure auth for client systems. What you'll do Conceptualize fast: embed with stakeholders, frame a business process … serve. Engineer the agent core: apply prompt engineering, context engineering, prompt caching, RAG/context-graph retrieval, memory, tool/function calling, MCP integration and multi-agent orchestration. Integrate to standards: connect agents into client ecosystems through proven integration patterns, standards-based APIs and secure authentication. Make reusability ...

Claude on Bedrock, Gemini, Azure OpenAI), selected per use case for quality, latency and cost. Interfaces: Tools and Model Context Protocol (MCP) for integration; standards-based APIs and secure auth for client systems. What you'll do Conceptualize fast: embed with stakeholders, frame a business process … serve. Engineer the agent core: apply prompt engineering, context engineering, prompt caching, RAG/context-graph retrieval, memory, tool/function calling, MCP integration and multi-agent orchestration. Integrate to standards: connect agents into client ecosystems through proven integration patterns, standards-based APIs and secure authentication. Make reusability ...

Claude on Bedrock, Gemini, Azure OpenAI), selected per use case for quality, latency and cost. Interfaces: Tools and Model Context Protocol (MCP) for integration; standards-based APIs and secure auth for client systems. What you'll do Conceptualize fast: embed with stakeholders, frame a business process … serve. Engineer the agent core: apply prompt engineering, context engineering, prompt caching, RAG/context-graph retrieval, memory, tool/function calling, MCP integration and multi-agent orchestration. Integrate to standards: connect agents into client ecosystems through proven integration patterns, standards-based APIs and secure authentication. Make reusability ...

system that solves it. Architecture, implementation, evaluation, and production operation. You are responsible for the system working, not just for your code compiling. Design context and retrieval strategies. What goes into the context window and what stays out is the most consequential design decision in an AI system. … thinking or external contributions in AI engineering (talks, writing, open source) Experience with multi‐agent coordination: task decomposition, handoff, shared state Practical experience with MCP (Model Context Protocol) or equivalent agent integration standards What We Are Not Looking For Pure ML researchers without production engineering experience. ...

bridge between cutting‐edge AI technologies and existing high‐code and low‐code platforms, the role focuses on AI enablement rather than foundational model building, ensuring intelligence is thoughtfully integrated into systems and workflows. The AI Engineer designs, develops, and assures AI-enabled solutions, improves automation efficiency, elevates engineering … automation platforms (e.g., Power Automate, n8n, Workato) by embedding intelligent processing and applying agentic patterns where relevant. Implement Model Context Protocol (MCP) servers for secure AI‐to‐system connectivity. Lead AI‐based document parsing and intelligent data extraction initiatives. Contribute to educating and enabling Enterprise Capabilities areas ...

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 ...

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 ...

distributed agent platform by integrating the Go-spiffe library with gRPC to enforce mTLS-based identity and authorization between agent runtimes, tool servers, and MCP (Model Context Protocol) proxies. 5. Building and operating containerized AI microservices including model-invocation gateways, MCP proxy layers, and webhook-driven … Contributing to the design and development of product features as part of a cross-functional engineering team, including OAuth-based third-party integration abstractions, MCP tool proxies, and webhook-driven event triggers for AI agents. 8. Collaborating with enterprise customers and internal teams to gather requirements, translate business needs into ...

team's work spans the full surface of how Multiverse operates. You own the technical architecture of our agentic operating system: the agent orchestration, context strategy, tool integrations, evaluation framework, and production operation. Your design decisions shape what is possible for human and AI teams at Multiverse Ship production … Published thinking or external contributions in AI engineering (talks, writing, open source) Experience designing platform layers that other teams build on Practical experience with MCP (Model Context Protocol) or equivalent agent integration standards What We Are Not Looking For Pure ML research without production engineering experience. ...

agent platforms (e.g. Amazon Bedrock, Microsoft Agent Framework, Claude Agent SDK), or comparable tools, including standards such as Model Context Protocol (MCP) for connecting agents to tools and data. Experience with retrieval systems for agents: retrieval-augmented generation, embedding models, vector databases, and long-term memory. Experience … support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about. Our hybrid work model BlackRocks hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting ...

have: Experience building CLIs with clean argument parsing, help text, and user‐friendly error handling Understanding of Model Context Protocol (MCP), have built MCP servers/clients, and understand how LLMs invoke tools and interact with external systems Experience with Redis Streams, event‐driven architectures, or real ...

client data into reliable pipelines, and turn those pipelines into production AI systems that deliver measurable business value. You will own the data and model layers of our client projects: designing and building the pipelines that feed AI systems, developing and deploying ML and LLM‐powered solutions, and standing … LangGraph, AutoGen, CrewAI), including agent evaluation and observability (e.g. LangSmith) Familiarity with tool/function calling and the Model Context Protocol (MCP) for connecting agents to external systems and data Experience with infrastructure‐as‐code and serverless data/ML deployment (Lambda, Cloud Run, Azure Functions) Exposure ...

Role Description gravity9 is expanding its Forward Deployed Engineering team to build production agentic AI systems for enterprise clients, in partnership with leading frontier-model providers. We already support clients from different verticals to have agentic and RAG systems live in production across healthcare, financial services, retail and global … observability. Strong advantage Anthropic certification (Claude Developer/Anthropic‐issued credential), an explicit advantage at shortlisting. Anthropic Agent SDK production experience, a significant bonus. MCP (Model Context Protocol): building servers and clients, tool exposure, auth patterns. Claude Code as an autonomous SDLC agent: sub‐agents, hooks, custom ...

architecture differentiates us from competitors like MuleSoft and BoomiInfluence enterprise architecture decisions and multi-year technology strategies at the executive levelAI, Agentic Automation & Enterprise MCP StrategyShape and guide customers' AI and agentic automation journeys, leveraging Workato's AI capabilities and ecosystemAdvise on the design and adoption of agent-based workflows … human-in-the-loop models, and decision automation frameworksPartner with customer executives to define enterprise MCP (Model Context Protocol) strategies including context management, secure AI orchestration, and governanceTranslate emerging AI capabilities into practical, scalable enterprise use cases that drive measurable business outcomesPosition Workato as the integration ...

similar).Experience with GenAI/LLM systems in a production context (RAG, prompt orchestration, evaluation, guardrails, cost/latency optimisation).Exposure to MCP (Model Context Protocol) and tool-based/function-calling architectures. Experience deploying and operating machine learning models/MLOps pipelines (e.g. model ...

. Experience with GenAI/LLM systems in a production context (RAG, prompt orchestration, evaluation, guardrails, cost/latency optimisation). Exposure to MCP (Model Context Protocol) and tool‐based/function‐calling architectures. Experience deploying and operating machine learning models/MLOps pipelines (e.g. model ...

role is engineering AI agents and agentic workflows. You will design how agents use trusted knowledge, approved tools, Model Context Protocol (MCP) services, approvals, human hand-offsand safe failure paths. You will ensure that evaluation, observability, identity,permissionsand data boundaries are built into delivery rather than added … agents and agentic workflows using trusted knowledge, tools, actions, approvals, human hand-offs,evaluationand safe failure paths. Design and implement integrations with approved MCP servers and lead development of MCP tools or services using secure, reusable patterns. Integrate Power Platform and AI solutions with Microsoft 365, SharePoint, Microsoft Graph, Azure ...

Apply Prompt Engineering and Context Engineering techniques to optimise AI performance and accuracy. Implement AI solutions using frameworks such as LangChain , LangGraph , and MCP . Integrate AI services and enterprise platforms through REST APIs and cloud-native architectures. Deliver scalable, secure, and reliable solutions using Python … Natural Language Processing (NLP) Prompt Engineering , Context Engineering AI Agents , Agentic AI , Multi-Agent Systems LangChain , LangGraph , Model Context Protocol (MCP) RAG , Embeddings , Vector Databases Python , SQL , REST APIs Git , CI/CD Cloud Platforms (Azure, AWS, or GCP) LLM & AI Agent Testing and Evaluation Desirable ...

implementation of scalable, secure and resilient cloud architectures.* Work with DevOps engineers to enhance CI/CD pipelines, automated testing and deployment processes.* Model and optimise data (AWS Redshift and Aurora PostgreSQL).**Be a leader*** Providing technical leadership and direction for the Royalty development team.* Orchestrate development … digital content domains.* Knowledge of microservices and event-driven architectures.* Experience with Infrastructure as Code (e.g. CloudFormation, CDK, Terraform).* Any experience with MCP (Model Context Protocol) and/or MLOps (e.g. model deployment pipelines, monitoring and lifecycle management) is highly desirable.* Understanding of compliance requirement ...

implementation of scalable, secure and resilient cloud architectures.* Work with DevOps engineers to enhance CI/CD pipelines, automated testing and deployment processes.* Model and optimise data across SQL and NoSQL stores.**Be Collaborative*** Drive code quality: write clean, efficient, well-documented and reusable code.* Participate in code reviews … delivering systems on GCP.* Knowledge of microservices and event-driven architectures.* Experience with Infrastructure as Code (e.g. CloudFormation, CDK, Terraform).* Any experience with MCP (Model Context Protocol) and/or MLOps (e.g. model deployment pipelines, monitoring and lifecycle management) is highly desirable.* Understanding of compliance ...