1 to 25 of 152 Remote/Hybrid Permanent Model Context Protocol Jobs

solutions, including 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 … with both is 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 ...

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. ...

whether that is an agent, a RAG pipeline, a document processing system, or something elseIntegrate foundation models (via API) into business applications and workflowsDevelop MCP (Model Context Protocol) servers and tool integrations where agent-based approaches are appropriateBuild RAG pipelines that surface accurate, attributed answers from internal … design• Experience building and shipping more than one type of AI system Strong proficiency in Python and REST API development Software Engineering & Integration• MCP (Model Context Protocol) server development and tool routing Building APIs and microservices to expose AI capabilities Integrating AI systems with enterprise tools ...

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 ...

incidents via telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails and security controls (SCPs/IAM boundaries … . Applying AI in CI/CD, observability, and incident response using AWS Bedrock/SageMaker and Model Context Protocol (MCP). Hands-on Agile delivery experience, actively participating in stand-ups and sprint ceremonies. Why Choose Fitch: Hybrid Work Environment: 2 to 3 days a week ...

incidents via telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails and security controls (SCPs/IAM boundaries … . Applying AI in CI/CD, observability, and incident response using AWS Bedrock/SageMaker and Model Context Protocol (MCP). Hands-on Agile delivery experience, actively participating in stand-ups and sprint ceremonies. Why Choose Fitch: Hybrid Work Environment: 2 to 3 days a week ...

will ideally have the following attributes: Experience building multi-agent workflows and autonomous AI systems Knowledge of the Model Context Protocol (MCP) and AI integration patterns Experience with vector databases such as Pinecone, Weaviate, FAISS, or Azure AI Search Experience working with OpenAI and other leading foundation … environments Developing multi-agent workflows to automate complex business processes Implementing AI orchestration using modern frameworks and the Model Context Protocol (MCP) Designing and implementing Retrieval-Augmented Generation (RAG) solutions using vector databases Building scalable AI services and data processing pipelines using Python Developing real-time ...

this role. Working with ML flow. Designing developing and testing agent build in Google ADK Working with Model Context Protocol (MCP) and creating servers. Other technology we use includes Neo4j, Postgres, Kafka and libraries such as FAST API. Build and maintain CI/CD pipelines to support … others can follow them. Generative AI: Familiarity with GenAI concepts including system prompts, Agent Development Kit (ADK), and Model Context Protocol (MCP) for data and service sharing. Google ADK: Hands‐on experience using Google ADK. Neo4j or other graph databases Team Leadership: Experience managing or coordinating software ...

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 ...

abstract, it’s visible. In this role, you will: Lead the engineering of production-grade products and features for AI agents, including LLM proxies, MCP server orchestration, and A2A protocol governance. Translate the "agent-first" vision into robust technical solutions, leveraging our API and Event management pillars to provide …/ML concepts and how they intersect with API infrastructure - particularly AI agents, A2A protocol, and Model Context Protocol (MCP) - to inform technical direction AI at Gravitee is not about shortcuts - it is about working smarter, faster, and more sustainably at scale. Essential Skills A strong ...

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 ...

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 ...

experience designing and implementing multi‐agent architectures (task decomposition, coordination, orchestration, and agent‐to‐agent (A2A) interaction patterns) Model Context Protocol (MCP) & Integrations: Experience integrating agents with enterprise tools and data sources using MCP or equivalent context‐sharing patterns Knowledge Graphs & Reasoning: Building and leveraging knowledge … graphs for context enrichment, reasoning, and workflow automation RAG & Knowledge Systems: End‐to‐end RAG pipelines using enterprise search + vector stores (e.g., Elastic, Pinecone) with grounding, evaluation, and optimization Model Lifecycle & Governance: Model evaluation, monitoring, prompt/version control, and Responsible AI/MRM compliance Enterprise ...

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. ...

impact and value for Cigna, advising senior leadership on AI strategy, feasibility and adoption paths. AI ArchitectureDefine architectural patterns and standards to support AI model lifecycle management, AI and data pipelines, feature engineering, and associated design artefacts. Architect and own enterprise-scale Generative AI platforms supporting multiple business … LLMs), embeddings, prompt engineering - Retrieval-Augmented Generation (RAG), Knowledge bases and Multimodal embeddingsAgentic AI workflows and tool calling - Model Context Protocol (MCP) concepts and context managementKnowledge on foundational models and inference profiles, regional hosting and restrictions of various models and be able to identify the right ...

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. ...

complex software engineering workflows. Tasks may involve debugging, feature implementation, code refactoring, performance optimization, and working with Model Context Protocol (MCP) tools. No prior AI experience is required — your technical expertise is what matters. Responsibilities Design and develop Reinforcement Learning environments that evaluate AI models on realistic … Develop reproducible environments with deterministic verification and golden reference solutions . Design workflows that require AI agents to discover and reason over information using MCP tools and real MCP servers . Evaluate AI-generated software solutions for correctness, maintainability, performance, and scalability . Apply strong knowledge of algorithms, data structures ...

complex software engineering workflows. Tasks may involve debugging, feature implementation, code refactoring, performance optimization, and working with Model Context Protocol (MCP) tools. No prior AI experience is required — your technical expertise is what matters. Responsibilities Design and develop Reinforcement Learning environments that evaluate AI models on realistic … Develop reproducible environments with deterministic verification and golden reference solutions . Design workflows that require AI agents to discover and reason over information using MCP tools and real MCP servers . Evaluate AI-generated software solutions for correctness, maintainability, performance, and scalability . Apply strong knowledge of algorithms, data structures ...

complex software engineering workflows. Tasks may involve debugging, feature implementation, code refactoring, performance optimization, and working with Model Context Protocol (MCP) tools. No prior AI experience is required — your technical expertise is what matters. Responsibilities Design and develop Reinforcement Learning environments that evaluate AI models on realistic … Develop reproducible environments with deterministic verification and golden reference solutions . Design workflows that require AI agents to discover and reason over information using MCP tools and real MCP servers . Evaluate AI-generated software solutions for correctness, maintainability, performance, and scalability . Apply strong knowledge of algorithms, data structures ...

complex software engineering workflows. Tasks may involve debugging, feature implementation, code refactoring, performance optimization, and working with Model Context Protocol (MCP) tools. No prior AI experience is required — your technical expertise is what matters. Responsibilities Design and develop Reinforcement Learning environments that evaluate AI models on realistic … Develop reproducible environments with deterministic verification and golden reference solutions . Design workflows that require AI agents to discover and reason over information using MCP tools and real MCP servers . Evaluate AI-generated software solutions for correctness, maintainability, performance, and scalability . Apply strong knowledge of algorithms, data structures ...

complex software engineering workflows. Tasks may involve debugging, feature implementation, code refactoring, performance optimization, and working with Model Context Protocol (MCP) tools. No prior AI experience is required — your technical expertise is what matters. Responsibilities Design and develop Reinforcement Learning environments that evaluate AI models on realistic … Develop reproducible environments with deterministic verification and golden reference solutions . Design workflows that require AI agents to discover and reason over information using MCP tools and real MCP servers . Evaluate AI-generated software solutions for correctness, maintainability, performance, and scalability . Apply strong knowledge of algorithms, data structures ...