51 to 75 of 97 Remote/Hybrid Model Context Protocol Jobs

strategiesWrite robust Python APIs and services (e.g., FastAPI), incorporating async execution, background jobs and containerized deploymentsIntegrate enterprise systems and tools using protocols such as MCP, A2A, OpenAPI, REST and gRPC, ensuring graceful degradation and retriesApply enterprise security and governance practices including RBAC, prompt safety checks, traceability and secrets managementImplement evaluation … trade-offs around cost, latency and accuracy to technical and non-technical audiencesNice to haveExperience using Azure AI Foundry or Microsoft Agent FrameworkKnowledge of MCP and A2A protocols for agent and tool interoperabilityHands-on work with vector databases like Pinecone, Weaviate, Qdrant or pgvectorFamiliarity with distributed systems, workflow engines (Temporal ...

retrieval evaluation for enterprise data groundingDevelop orchestration engines supporting multi-step planning, delegation, and fallback paths for agent workflowsImplement integration and communication patterns via MCP, A2A, OpenAPI, REST, and gRPCBuild production-grade Python APIs and microservices integrating with enterprise systems and AI servicesApply observability and monitoring solutions (Langfuse, Arize, Grafana … evaluation methodologiesExperience with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel)Familiarity with orchestration strategies like planner/executor and tool callingKnowledge of MCP, A2A protocols, and OpenAPI-based integration methodsStrong experience with cloud environments, ideally Azure (Azure OpenAI, AI Foundry, AI Search)Competence in containerized deployments, CI/ ...

systems. Hands-on experience with modern agent frameworks such as Strands Agents, LangGraph or the Claude Agent SDK, and with interoperability standards such as MCP and A2A.Strong cloud-native expertise on AWS, especially Amazon Bedrock and Bedrock AgentCore, alongside SageMaker, Lambda and Step Functions, with CDK or equivalent IaC.Hands … publishing, entertainment or other content-led industry. Proven experience building and operating agentic AI systems in production, including multi-agent orchestration, tool use via MCP, agent memory and agentic RAG.Depth in NLP, such as information extraction, classification, summarisation and semantic search, or fine-tuning LLMs. Experience building shared AI platforms ...

DevOps, RBAC and cost controls. Solid software engineering fundamentals: Clean Code (SOLID, DRY), DDD, modular architecture, TDD and code quality tooling. Desirable: RAG pipelines, MCP, LLM integration (OpenAI, Gemini, Hugging Face models), LangSmith, TruLens, and agentic frameworks such as LangChain, CrewAI, Autogen, OpenAI Agents and Google ADK. … Developer, React Developer, Next.js Developer, TypeScript Developer, Azure OpenAI, Vertex AI, LangChain, LangGraph, CrewAI, Autogen, OpenAI Agents SDK, Google ADK, RAG, retrieval augmented generation, MCP, LangSmith, TruLens, prompt engineering, Docker, Kubernetes, AKS, GCP, Azure DevOps, GitHub Actions, PostgreSQL, BigQuery, TDD, DDD. Deerfoot Recruitment Solutions Ltd is a leading independent tech ...

team depends on: Nexus, our agentic workspace, where employees build, test, run, and manage governed AI applications, agents, and shared skills; Accio, our centralised MCP server, which acts as a passthrough and logic centre for enterprise datasets, consuming other MCP servers and presenting them through one governed interface … application gives the firm more control, lower cost, or capability no vendor sells. Your toolkit spans Python and SQL, LLMs and agent frameworks, MCP, Azure AI Foundry through the AI Team's model gateway, Snowflake and Microsoft Fabric, and Azure with Terraform, Docker, and CI/CD. AI Engineering ...

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 ...

oriented with great documentation skills Excellent oral and written communication skills with a keen sense of customer service Experience with AI tooling. (experience developing MCP servers or other AI connectors is a big plus) Scantrust Offers A small but fast-growing international company Laid-back office in the heart ...

Extra Points for... Familiarity with Google Cloud AI services (Gemini Enterprise Agent Platform, ADK)AI evaluation or AI security experience. Agentic development experience (MCP, multi-agent systems). RAG implementation experience. Cloud DevOps or Terraform experience. Prior experience in iGaming, fintech, or another regulated industry. AI governance experience or interest. ...

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 ...

Skills/Tech Experience Required: GCP Python Vertex AI/Gemini LangChain/LangGraph RAG/Vertex AI RAG Engine Multi-Agent Architectures MCP/A2A Terraform Kubernetes UK based for tax purposes If you're a hands-on AI/Data Engineer looking to work on cutting-edge Google ...

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 ...

traditional machine learning solutions. Practical experience with modern agent frameworks such as LangGraph, Strands Agents or Claude Agent SDK, alongside interoperability standards including MCP and A2A. Strong AWS cloud engineering experience, particularly Amazon Bedrock, Bedrock AgentCore, SageMaker, Lambda and Step Functions, with Infrastructure as Code using AWS CDK or equivalent. … engineering, automated testing and AI-assisted development. Desirable Experience: Experience building and operating production-grade agentic AI systems, including multi-agent orchestration, agent memory, MCP-based tool integration and agentic RAG. Strong NLP expertise, including semantic search, summarisation, information extraction, classification or LLM fine-tuning. Experience developing shared AI platforms ...

LLMs * Retrieval Augmented Generation (RAG) * Multi-Agent Systems * MLOps/LLMOps * LangGraph, LangChain, Semantic Kernel, CrewAI or AutoGen * OpenAI Agents, Microsoft Copilot Studio and MCP * Azure, AWS or GCP Education * 2:1 degree or above from a Russell Group university in Computer Science, Artificial Intelligence, Mathematics, Physics, Engineering … Engineering, Agentic AI, AI Agents, Generative AI, LLMs, Machine Learning, Data Science, Platform Engineering, LangGraph, LangChain, Semantic Kernel, CrewAI, OpenAI Agents, Microsoft Copilot Studio, MCP, MLOps, RAG, SaaS, Cambridge. ...

designing bespoke architectures, writing code, and engineering prompts to deliver tangible business outcomes. You will leverage Docusign's IAM Platform, Docusign and third Party MCP servers, APIs, and third party integrations with leading AI ecosystems (like OpenAI, Microsoft CoPilot, and Claude) to optimize enterprise agreement lifecycles against contract populations exceeding … Agreement Management business processesDesign, build, and deploy AI enabled workflows and solutions that integrate Docusign AI capabilities including but not limited to, Docusign's MCP Server and APIs, Docusign Web Forms backed by APIs to third party systems, Custom Extractions, Docusign skills in 3rd party agentic platforms (e.g. Docusign ...

debug agents, and ship. We will verify this in the interview process Deep, current applied AI capability: production agentic systems, RAG and Graph RAG, MCP, agent runtimes, and fluency across model providers rather than loyalty to one Eval fluency. You can articulate and build an evaluation strategy … function calling, structured outputs, context and token management, prompt architecture Agentic systems: designing, hosting, and operating autonomous and semi-autonomous agents in production; MCP servers and clients; orchestration frameworks such as LangGraph, Pydantic AI, or provider-native SDKs; sandboxing, permissioning, and human-in-the-loop design Retrieval and knowledge ...

agent-to-agent communication. Production experience with agent frameworks such as LangGraph, Microsoft Foundry, AWS Bedrock, CrewAI, AutoGen, or comparable orchestration tooling, plus MCP or similar protocols. Strong grounding in evaluation, observability and reliability for AI systems: eval suites, tracing, guardrails, monitoring and incident response for agentic workloads. Hands … experience with the Claude API, Claude Code, MCP, GitHub's AI tooling, or equivalent leading AI platforms and tooling, in production. A degree in a related field, or equivalent practical experience. What Version 1 gives you A role built around the craft, in front of the customer. This track exists ...

agent-to-agent communication. Production experience with agent frameworks such as LangGraph, Microsoft Foundry, AWS Bedrock, CrewAI, AutoGen, or comparable orchestration tooling, plus MCP or similar protocols. Strong grounding in evaluation, observability and reliability for AI systems: eval suites, tracing, guardrails, monitoring and incident response for agentic workloads. Hands … experience with the Claude API, Claude Code, MCP, GitHub's AI tooling, or equivalent leading AI platforms and tooling, in production. A degree in a related field, or equivalent practical experience. What Version 1 gives you A role built around the craft, in front of the customer. This track exists ...

agent-to-agent communication. Production experience with agent frameworks such as LangGraph, Microsoft Foundry, AWS Bedrock, CrewAI, AutoGen, or comparable orchestration tooling, plus MCP or similar protocols. Strong grounding in evaluation, observability and reliability for AI systems: eval suites, tracing, guardrails, monitoring and incident response for agentic workloads. Hands … experience with the Claude API, Claude Code, MCP, GitHub's AI tooling, or equivalent leading AI platforms and tooling, in production. A degree in a related field, or equivalent practical experience. What Version 1 gives you A role built around the craft, in front of the customer. This track exists ...

agent-to-agent communication. Production experience with agent frameworks such as LangGraph, Microsoft Foundry, AWS Bedrock, CrewAI, AutoGen, or comparable orchestration tooling, plus MCP or similar protocols. Strong grounding in evaluation, observability and reliability for AI systems: eval suites, tracing, guardrails, monitoring and incident response for agentic workloads. Hands … experience with the Claude API, Claude Code, MCP, GitHub's AI tooling, or equivalent leading AI platforms and tooling, in production. A degree in a related field, or equivalent practical experience. What Version 1 gives you A role built around the craft, in front of the customer. This track exists ...

understand edge cases and operational requirementsProduce lightweight technical documentation, diagrams and decision recordsQuality, reliability and AI operationsImplement evaluation frameworks and safety checks across model and agent behaviourBuild monitoring, logging, tracing and incident-handling patternsApply governance, risk and compliance principles to AI deploymentsSupport release cycles, environments and operational readinessOwn reliability … applied data engineeringStrong hands-on experience with LLMs, embeddings, RAG, retrieval stacks and vector storesPractical experience building multi-agent systems, agent orchestration or MCP-style tool patternsStrong Python, with a track record of production-grade workflowsExperience with at least one cloud AI ecosystem: Azure OpenAI, Google Vertex AI, AWS Bedrock ...

cases and operational requirements Produce lightweight technical documentation, diagrams and decision records Quality, reliability and AI operations Implement evaluation frameworks and safety checks across model and agent behaviour Build monitoring, logging, tracing and incident-handling patterns Apply governance, risk and compliance principles to AI deployments Support release cycles, environments … data engineering Strong hands-on experience with LLMs, embeddings, RAG, retrieval stacks and vector stores Practical experience building multi-agent systems, agent orchestration or MCP-style tool patterns Strong Python, with a track record of production-grade workflows Experience with at least one cloud AI ecosystem: Azure OpenAI, Google Vertex ...

partner with the owning engineering team to scope and build it — hands-on throughout, not handing off a ticketGet into the data pipelines, model serving, retrieval and evaluation behind AI-backed features, and the integrations that put them into a real workflowShip a working first version fast, then harden … LLMs in production applications — model APIs, auth, gateways, reliability, latency, cost, observabilityAgentic systems: agentic applications using tools, APIs and orchestration frameworks. Hands-on MCP strongly preferredRetrieval and RAG: production retrieval systems — embeddings, vector stores, indexing, retrieval quality, evaluationAPIs and enterprise integration: REST, auth/authz, data contracts ...

tools, and enterprise applications. Design, build, test, and scale AI concepts, internal products, mini apps, and reusable enterprise solutions across AI workflows, API and MCP style integrations, AI coding assistants, and agentic use cases. Contribute to Arm's emerging technical AI roadmap by assessing models, frameworks, whitepapers, open-source projects … with LLM and agentic patterns, including retrieval, orchestration, tool use, evaluation, guardrails, and governed production deployment. Solid understanding of AI architecture, cloud platforms, APIs, model-agnostic design, reusable frameworks, and scalable AI engineering practices. Demonstrated ability to turn emerging research, whitepapers, open‐source developments, and new tools into practical ...

internal and external data, curating it into views that answer the questions a desk actually asks, and making it reusable through Accio, our centralised MCP server. The most advanced work is investment engineering: building quantitative capability on Nexus, our agentic workspace, and taking it from one desk to a firm … wide offering such as relative-value signal generation. Your toolkit spans Python and SQL, LLMs and agent frameworks, MCP, Azure AI Foundry through the AI Team's model gateway, Snowflake, and Azure with Terraform, Docker, and CI/CD.What success looks likeYou ship. What you build reaches production ...

internal and external data, curating it into views that answer the questions a desk actually asks, and making it reusable through Accio, our centralised MCP server. The most advanced work is investment engineering: building quantitative capability on Nexus, our agentic workspace, and taking it from one desk to a firm … wide offering such as relative-value signal generation. Your toolkit spans Python and SQL, LLMs and agent frameworks, MCP, Azure AI Foundry through the AI Team's model gateway, Snowflake, and Azure with Terraform, Docker, and CI/CD.What success looks likeYou ship. What you build reaches production ...