276 to 300 of 586 Model Context Protocol Jobs

least one object oriented programming language (JavaScript/TypeScript, Python, Java, C#, etc) You have hands‐on experience with GenAI (e.g. Playwright with MCP). Experience with AI‐assisted coding tools (e.g., GitHub Copilot, Claude) is required, knowledge of LangChain or LangGraph, and cloud environments is a plus. You love ...

Demonstrable AI engineering depth. You can show real systems where you made substantive decisions about agent harnesses, evals, hallucination containment, performance, agent sandboxing or MCP/tool design. Strong product engineering and technical judgment. You ship across interface, backend, data and deployment, reason from first principles and choose tools deliberately. ...

accelerate pipeline development, data analysis, and automation Skills & agents: Hands-on experience building AI skills and agents within the Amazon internal ecosystem (AIM, MCP integrations), or a strong desire to learn Amazon Q & Quick AI Features: Familiarity with surfacing data insights through AI-powered experiences and understanding how these tools ...

platform modernisation or reliability initiatives in scale‐up or regulated environments, Operator development, CRD automation, eBPF, Cilium, policy‐as‐code with OPA or Kyverno, MCP and A2A orchestration patterns, Agent Gateways and Registries, secure containers, sandboxing, confidential computing, Spark, Databricks, Data Mesh, Go, Python, TypeScript, open‐source or CNCF community ...

move into defensive Product Security. Experience using AI or agentic AI within security engineering, code review or vulnerability triage. Experience securing LLMs, AI agents, MCP or other AI-enabled systems. Cloud, container or Kubernetes security experience, plus exposure to C#, .NET, Python, Bash or PowerShell. This Role Probably ...

DAST adoption and quality, from tool tuning to severity calibration and developer-facing triage guidance Support product teams adopting AI, including LLMs, SLMs, and MCP, giving you visibility into work most security roles wouldn't touch What Makes You a Great Fit Hands-on product or application security experience, embedding ...

DAST adoption and quality, from tool tuning to severity calibration and developer-facing triage guidance Support product teams adopting AI, including LLMs, SLMs, and MCP, giving you visibility into work most security roles wouldn't touch What Makes You a Great Fit Hands-on product or application security experience, embedding ...

audit trails, version control and ownership 4. AI and Automation Development Design, build and deploy AI-enabled workflows using LLMs, developer CLI tools, APIs, MCP and automation platforms Connect systems including ERP, ecommerce, CRM, customer service and reporting platforms Decide where to use AI, deterministic rules or human review based ...

London. Even Better If You Bring • Hands-on experience administering AI coding or agent tools, including Claude Code, GitHub Copilot or Codex. • Experience configuring MCP servers, connectors, permissions and access controls. • Familiarity with emerging agentic AI infrastructure and its associated security considerations. • Experience working with Netskope. • Hands-on Netskope CASB ...

productionize core components of our AI platform – including: LLMs and the surrounding ecosystem (e.g., vector DBs, prompt tuning, etc.)Agentic frameworksCore agent capabilities like MCP/cross-platform tool use, web browsing, computer useEnforce technical discipline and operational excellence for all of our AI productsRapidly iterate on AI products based ...

productionize core components of our AI platform – including: LLMs and the surrounding ecosystem (e.g., vector DBs, prompt tuning, etc.)Agentic frameworksCore agent capabilities like MCP/cross-platform tool use, web browsing, computer useEnforce technical discipline and operational excellence for all of our AI productsRapidly iterate on AI products based ...

least one object oriented programming language (JavaScript/TypeScript, Python, Java, C#, etc)You have hands-on experience with GenAI, (e.g. Playwright with MCP). Experience with AI-assisted coding tools (e.g., GitHub Copilot, Claude) is required, knowledge of LangChain or LangGraph, and cloud environments is a plus. You love ...

least one object oriented programming language (JavaScript/TypeScript, Python, Java, C#, etc) You have hands‐on experience with GenAI, (e.g. Playwright with MCP). Experience with AI-assisted coding tools (e.g., GitHub Copilot, Claude) is required, knowledge of LangChain or LangGraph, and cloud environments is a plus. You love ...

controls, or building multi‐tenant platforms across brands and regions Experience shipping LLM‐backed features to real users (retrieval, grounding and evaluation), or with MCP, agent frameworks or tool‐calling in production Why Join Us? At Deliveroo, you’ll do work that matters—solving real‐world problems in a three ...

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 ...

write. You go beyond prompt-and-paste. You’ve built or configured something (agentic workflows, automated triage or review, evaluation harnesses, custom tooling, MCP integrations) that made a repeatable part of engineering measurably faster or more reliable. You know where AI output cannot be trusted. A generated test that asserts ...

command of APIs, webhooks, and data structures (JSON, REST, GraphQL) — able to design and troubleshoot integrations confidently. Even better if you have experience with MCP Servers. Hands‐on experience with low‐code orchestration tools (Zapier, Make, n8n, Workato) and CRM automation (HubSpot, Salesforce). Proficiency in scripting (JavaScript and/ ...

TypeScript) is a welcome plus, not a requirement. Enterprise Platform Fluency: You bring hands-on experience with the building blocks of modern enterprise APIs (MCP, CLIs, and OAuth) and know how to wield them to build secure, extensible integrations. Cross-Team Leadership: You have a track record of leading projects ...

frameworks using network documentation, alarms, topology, inventory, KPIs, trouble tickets, procedures, configuration data, and operational knowledge.* Develop multi-agent workflows using LangChain, LangGraph, MCP, or similar frameworks.* Implement vector search, semantic retrieval, graph-enhanced retrieval, and hybrid search patterns.* Develop AI agents for fault diagnosis, root-cause analysis, KPI analysis … systems.* Strong Python programming skills.* Experience with ML fundamentals, deep learning concepts, embeddings, transformers, and LLM architectures.* Experience using LangChain, LangGraph, LlamaIndex, AutoGen, MCP, or similar AI frameworks.* Experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, ChromaDB, or equivalent.* Experience with graph databases, knowledge graphs, or Graph APIs. ...

others: Agentic AI & LLM Engineering Design and build production‐grade agentic systems using major LLM SDKs and agent frameworks; deep knowledge of RAG, MCP servers and prompt engineering at scale. Strong opinions on secure, resilient enterprise deployment of LLM‐powered systems; current knowledge of the latest model capabilities … product stacks. Machine Learning Engineering End-to‐end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit‐learn, PyTorch, XGBoost) and cloud‐native ML services (SageMaker, Azure ML, Vertex AI). Architecture and delivery ...

others: Agentic AI & LLM Engineering: Design and build production-grade agentic systems using major LLM SDKs and agent frameworks; deep knowledge of RAG, MCP servers and prompt engineering at scale. Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities … product stacks. Machine Learning Engineering: End-to-end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Software Engineering: Production ...

others: Agentic AI & LLM Engineering: Design and build production-grade agentic systems using major LLM SDKs and agent frameworks; deep knowledge of RAG, MCP servers and prompt engineering at scale. Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities … product stacks. Machine Learning Engineering: End-to-end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Software Engineering: Production ...

layer connecting agentic systems to enterprise commerce stacks (OMS, PIM, DAM, CRM, payments, pricing, fulfilment) via API gateways, event buses, and emerging agentic protocols (MCP, A2A, ACP, UCP) Lead build vs. buy decisions across LLM platforms, orchestration frameworks, vector stores, and agentic workbenches; design multi-model routing strategies … Azure; CI/CD and cloud-native architecture Demonstrated leadership of complex, multi-region enterprise programs Nice to Have Experience with agentic commerce protocols: MCP, A2A, ACP (OpenAI), UCP (Google) Hyperscaler agentic platforms: Google Vertex AI/Agent Dev Kit, Azure AI Foundry, AWS Bedrock Agents GEO/AEO content ...

technologies including Azure OpenAI, Azure AI Foundry, Foundry Agents and Azure AI Search . Building LLM-powered applications, RAG architectures, agentic workflows and MCP integrations . Deploying secure and scalable applications within Microsoft Azure. Working directly with customers to translate business challenges into practical technical solutions. Using tools such … turn them into structured, scalable solutions. Microsoft AI experience Experience across the Microsoft AI ecosystem would be particularly valuable, including: Foundry Agents Cognitive Services MCP AI evaluation, testing and observability Previous experience working within a Microsoft Partner, consultancy, MSP or professional services environment would also be highly advantageous. Why this ...

design, development and deployment of AI-integrated applications using modern full-stack technologies. Build features powered by LLMs, agentic workflows, RAG patterns and MCP integrations. Work directly with customers to shape requirements and translate them into working software. Integrate Azure AI services such as Azure OpenAI, Cognitive Services, Azure … mentor others. Excellent communication and stakeholder management skills. Comfortable working autonomously and shaping ambiguity into structured delivery. Desirable Azure AI Engineer certification. Understanding of MCP, vector databases and AI evaluation/testing approaches. Experience mentoring or leading small development teams. Why Candidates Are Attracted to This Environment The organisation offers ...