26 to 50 of 253 Model Context Protocol Jobs

rapid deployment of GenAI applications (including Retrieval-Augmented Generation (RAG) pipelines) and agents with planning, memory, and workflow orchestration Implement tools and frameworks for model versioning, experiment tracking, and lifecycle management Develop systems to monitor model performance and address data and model drift Recommend best practices … Familiarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP) Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK) Strong communication skills for both technical and non-technical audiences Preferred qualifications, capabilities ...

rapid deployment of GenAI applications (including Retrieval-Augmented Generation (RAG) pipelines) and agents with planning, memory, and workflow orchestration Implement tools and frameworks for model versioning, experiment tracking, and lifecycle management Develop systems to monitor model performance and address data and model drift Recommend best practices … Familiarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP) Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK). Strong communication skills for both technical and non-technical audiences. Preferred qualifications, capabilities ...

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 ...

scalable, self-service solutions for documentation, SDKs, configurations, and pipelines to enable rapid deployment of GenAI applications and agents Implement tools and frameworks for model versioning, experiment tracking, and lifecycle management Develop systems to monitor model performance and address data and model drift Recommend best practices … Familiarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP) Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets Previous experience deploying and managing ML models Experience working ...

improve SEO, conversion rates, and user experience. Build production AI solutions using Vercel's AI SDK and AI Cloud—including conversational interfaces, production agents, MCP servers, and agentic workflows that transform customer operations. Embed with strategic customers to build production applications—working within their systems, understanding their constraints, and shipping … Core Web Vitals, with experience diagnosing and fixing LCP, CLS, and INP issues at scale. Have experience with Model Context Protocol (MCP), building MCP servers, or implementing complex tool‐use patterns in production AI applications. Have led enterprise AI transformation initiatives, including building production agents that automated ...

Multiverse works AI-native. The ways of working that make this role possible are constantly being refined. You contribute the patterns, tooling, and operating model, prove them in how your own team runs, and share what works with the wider org. What We Are Looking For Product Ownership … native org Experience in EdTech, regulated content, or domains where AI output quality has compliance or accreditation implications Practical experience with MCP (Model Context Protocol) or equivalent agent integration standards What We Are Not Looking For Traditional engineering managers who run delivery and ceremonies ...

architecture of the subscription lifecycle, including sign-up, trials, plan changes, upgrades, downgrades, proration, pauses, cancellations and win-back. Define and evolve the entitlements model that connects a customer’s billing status with the content and services they can access across web, mobile and connected television platforms. … Legal. AI-enabled engineering Apply our standards for using large language models and agentic tools across software design, development, testing and operations. Treat specifications, context, prompts, agent configurations and evaluation criteria as version-controlled engineering artefacts. Design and improve guardrails, evaluations and quality gates for AI-assisted development ...

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 … engineering bar, and grow the pod's agentic capability. Must Have Skills python LangGraph Open AI Agents SDK Model Context Protocol (MCP) Amazon Bedrock Large Language Models (LLMs ...

Large Language Model (LLM) integration and prompt engineering AI agents and agent orchestration Retrieval-Augmented Generation (RAG) Model Context Protocol (MCP) AI observability, experimentation and model evaluation Experience with cloud platforms, APIs, distributed systems and modern software engineering practices will help you succeed in this ...

infrastructure to accelerate AI solution development. Design and develop multi‐agent systems for orchestration, agent‐to‐agent communication, eval, memory, telemetry, and guardrails. Apply context and prompt engineering techniques to improve prompt‐based model performance. Develop and maintain tools and frameworks for prompt‐based agent evaluation, monitoring … with engineers, data scientists, and ML practitioners. Experience in customising and optimizing Github Copilot using VSCode Extension or Model Context Protocol (MCP). Experience with AWS and infrastructure‐as‐code tools such as Terraform. Experience in multi‐agent orchestration. Familiarity with MLOps practices, including CI/ ...

infrastructure to accelerate AI solution development. Design and develop multi-agent systems for orchestration, agent-to-agent communication, eval, memory, telemetry, and guardrails. Apply context and prompt engineering techniques to improve prompt-based model performance. Develop and maintain tools and frameworks for prompt-based agent evaluation, monitoring … with engineers, data scientists, and ML practitioners. Experience in customising and optimizing Github Copilot using VSCode Extension or Model Context Protocol (MCP) Experience with AWS and infrastructure‐as‐code tools such as Terraform. Experience in multi‐agent orchestration. Familiarity with MLOps practices, including CI/ ...

Systems RAG Retrieval Augmented Generation Prompt Engineering AI Evaluation AI Observability AI Governance Responsible AI AI Security Guardrails Model Context Protocol (MCP) Function Calling Tool Use AI Orchestration AI Platforms Experience with one or more: OpenAI Azure OpenAI Anthropic Claude Google Gemini AWS Bedrock Hugging Face LangChain ...

deliver. Develop prototypes and production components for client AI solutions: agent workflows, RAG pipelines, LLM integrations (Azure OpenAI, AWS Bedrock, Google Vertex, Anthropic), MCP-based tool integrations, and the governance and security controls around them. Deliver custom adapters and local tooling for regulated, cloud-restricted, or air-gapped environments where … leakage, agent permissioning, model and data security posture (AI-SPM/DSPM concepts). Familiarity with the Model Context Protocol (MCP), agent runtimes, or vector databases (e.g., Pinecone, Milvus, Weaviate, Chroma). Background in enterprise data governance, security, backup/resilience, or the Microsoft 365/ ...

Integrate Azure AI services (Azure OpenAI, Cognitive Services, Azure ML, AI Search) into production applications. Architect and build LLM-powered features, agentic workflows, and MCP (Model Context Protocol) integrations to a production standard. Work directly with clients to understand requirements, shape solutions, and translate them into working … build client confidence. Comfortable working autonomously and shaping ambiguity into repeatable, scalable delivery. Advantageous Azure AI Engineer certification or equivalent practical experience. Understanding of MCP, vector databases, and evaluation/testing approaches for AI systems. Experience mentoring or leading small development teams. Why BCN? Competitive salary with the ability ...

enterprise AI platform that powers AI products across the company. Develop scalable AI services supporting Agentic AI, Retrieval‐Augmented Generation (RAG), embeddings, vector search, model serving, and intelligent automation. Build orchestration layers that transform structured and unstructured enterprise data into reusable AI capabilities. Develop production‐ready AI applications using … experience. LLMs & Agentic AI Hands‐on experience building applications powered by Large Language Models (LLMs). Experience building Model Context Protocol (MCP) and Retrieval‐Augmented Generation (RAG) solutions, making use of embeddings, vector databases, and modern LLM orchestration frameworks. Experience building or contributing to agentic AI systems ...

context window limitations in LLM systems. Exposure to agent-based architectures and emerging protocols such as the Model Context Protocol (MCP). Experience with MLOps tools and platforms (e.g., MLflow, Amazon SageMaker, Google VertexAI, Databricks, BentoML, KServe, Kubeflow) #ICBCareer #ICBEngineering ABOUT US J.P. Morgan ...

embeddings, and fine-tuning strategies Implement orchestration pipelines using Semantic Kernel and LangGraph for multi-agent workflows Integrate tools, APIs, and enterprise systems using MCP (Model Context Protocol) or similar frameworks Design memory, state management, and context-aware agent behaviors Optimize performance, cost, and latency ...

engineering role, not a configuration one. As Salesforce grows into a serious AI platform, you'll be building with Agentforce, Einstein, Prompt Builder, Model Builder, and Data Cloud to create agents and AI-driven features that hold up under real workloads. The work varies a lot. … solutions for large-scale environments supporting hundreds or thousands of Salesforce users. • Nice to have: familiarity with the Model Context Protocol (MCP), vector search and embeddings, or Python for AI tooling. Consulting & Delivery • Proven experience translating complex business requirements and user stories into scalable technical solutions. • Experience ...

standardize AI agent development across teams. AIOps, Production Monitoring & Operations Establish monitoring, observability and operational governance for production AI workloads. Track agent performance, model latency, cost, prompt effectiveness, error rates and quality signals. Define alerting, incident response, RCA processes and production runbooks for AI applications. Troubleshoot AI agent issues … similar agent frameworks. Experience with Bedrock Knowledge Bases, vector databases such as OpenSearch, Pinecone or Weaviate, and embedding-based retrieval patterns. Experience with MCP (Model Context Protocol), enterprise tool integration and workflow automation. Knowledge of AI safety, guardrails, governance, responsible AI and GenAI FinOps. Experience integrating ...

Understanding of AI governance, security, privacy and responsible AI principles. Experience with Microsoft Copilot, Azure AI, AWS Bedrock, Model Context Protocol (MCP), knowledge graphs or enterprise search technologies would be an advantage—though it's not essential. Why Join Vix? This is an opportunity to shape ...

context window limitations in LLM systems. Exposure to agent-based architectures and emerging protocols such as the Model Context Protocol (MCP). Experience with MLOps tools and platforms (e.g., MLflow, Amazon SageMaker, Google VertexAI, Databricks, BentoML, KServe, Kubeflow) #J-18808-Ljbffr ...

loop that keeps programme design connected to what actually benefits the teams. Support the configuration and integration of agentic tooling within divisional environments – including MCP integration, IDE setup and workflow automation – to the point where teams can self‐serve and maintain it. Evaluate agentic tooling options – Cursor, Claude Code, GitHub … conversation from "this doesn’t work for us" to "let’s figure out why and how to fix it". Useful Experience Experience with MCP (Model Context Protocol) server configuration, tool integration or agentic workflow automation beyond IDE‐level tooling. Exposure to prompt engineering, agent orchestration ...

services and REST/GraphQL APIs using Java/Spring Boot (or equivalent modern Back End stack). Contribute to system architecture and data model design in collaboration with senior/lead engineers. Write clean, well-tested, maintainable code following TDD/BDD practices and team coding standards. Participate … strong aptitude to learn) building or integrating agents using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or the Model Context Protocol (MCP). Ability to design and expose Back End services as tools/functions callable by AI agents (tool schemas, function calling, structured outputs). Experience ...

Azure Machine Learning and AI Search, into production applications. Architect and build LLM-powered features, agentic workflows and Model Context Protocol (MCP) integrations to a production standard. Work directly with clients to understand requirements, shape solutions and translate them into working software. Provide technical leadership across engagements … turn ambiguity into repeatable, scalable delivery. It Would Be An Advantage If You Have Azure AI Engineer certification or equivalent practical experience. Knowledge of MCP, vector databases and evaluation or testing approaches for AI systems. Experience mentoring or leading small development teams. Why Apply? Industry-leading training and development through ...

support. Smartsheet is building a market-leading AI narrative anchored in organizational intelligence, agentic workflows, and the Model Context Protocol (MCP), and this role exists to make that narrative land with EMEA field teams and the enterprise buyers they serve. As a Sr. Product Marketing Manager … executives and solution engineers. Build and maintain the EMEA AI content suite in Smarsheet’s enablement platformHighspot: discovery slides, AI use‐case messaging guides, MCP value narratives, and competitive positioning against regional alternatives. Track enablement adoption through leading indicators including Gong keyword usage, Highspot engagement, and qualitative field feedback ...