26 to 50 of 81 Remote/Hybrid Model Context Protocol Jobs

Python, APIs, etc. Familiarity with AI-assisted development and agentic coding tools (Claude Code, Cursor, Codex) and the Model Context Protocol (MCP) is a plus Experience with web development and containerized software is a plus Strong sales acumen and proven experience partnering with AEs to drive ...

Azure OpenAI Design, develop and support secure REST APIs using C# and .NET Build and manage Azure Functions and serverless services Develop and support MCP Servers and AI integration services Design event-driven architectures using Azure Service Bus Manage APIs through Azure API Management Expose AI capabilities through secure, auditable … design and development Azure AI Foundry Azure OpenAI Event-driven architecture Azure integration engineering Secure API design Production support and operational ownership Desirable Experience MCP Servers Model Context Protocol Semantic Kernel Prompt Flow Agentic AI AI orchestration frameworks Copilot Studio Power Platform integrations RAG architectures AI governance ...

frameworks (e.g., LangChain, LlamaIndex) Experience in deep learning frameworks and front-end development Familiarity with Langfuse, Langsmith, or other LLM observability tools Understanding of Model Context Protocol and bias/hallucination mitigation techniques Previous success in integrating GenAI solutions into enterprise-scale systems Why Join Capco Deliver ...

CLIP and CLAP) across diverse, real-time sensor streams. To succeed, you must possess strong architectural intuition, deeply understanding the technical compromises inherent in model selection and able to identify the optimal agentic design pattern for specific tasks Your responsibilities will include: Building core agentic product features; researching, planning … foundations of core ML algorithms, paired with hands‐on experience using deep learning frameworks (PyTorch, JAX, TensorFlow), agentic orchestration ecosystems (LangGraph, Google ADK), and Model Context Protocol tooling (RustMCP) Strong written and verbal communication skills to document your work effectively and present it to relevant stakeholders ...

infrastructure, data pipelines, orchestration layers, integration patterns, and governance controls. Develop reference architecture for agentic AI systems and multi‐agent workflows, establishing standards for MCP and model‐context protocols. Create AI reference architectures for investment and front‐to‐back office use cases. Drive integration of AI capabilities with … core data platforms and content platforms, leveraging RAG and MCP to unlock proprietary data assets. Governance & Risk: Design and operationalize AI governance, covering model risk management, explainability, bias monitoring, data lineage, and regulatory compliance. Evolve model evaluation and selection criteria for frontier and open‐weight models, balancing capability ...

sharing infrastructure, governance, comms, and the firm‐wide adoption dashboard. Your primary toolkit today spans the modern AI engineering stack – coding agents, agentic harnesses, MCP, in‐platform AI in Snowflake and Databricks, and the JHOS/NEXUS platform Percepta is building – but the firm’s AI strategy is platform‐agnostic. … Foundry, APIM, Cortex, Databricks Genie Code, and the forthcoming LLM Gateway Stay current with the rapidly evolving AI engineering landscape – coding agents, agentic harnesses, MCP, model releases, benchmarks, DORA and industry research – and translate what matters into practical curriculum changes Collaborate with Technology, Security, and Responsible AI teams ...

sharing infrastructure, governance, comms, and the firm‐wide adoption dashboard. Your primary toolkit today spans the modern AI engineering stack—coding agents, agentic harnesses, MCP, in‐platform AI in Snowflake and Databricks, and the JHOS/NEXUS platform Percepta is building— but the firm’s AI strategy is platform‐agnostic. … Foundry, APIM, Cortex, Databricks Genie Code, and the forthcoming LLM Gateway Stay current with the rapidly evolving AI engineering landscape—coding agents, agentic harnesses, MCP, model releases, benchmarks, DORA and industry research—and translate what matters into practical curriculum changes Collaborate with Technology, Security, and Responsible AI teams ...

this position you will play a key part in: Designing and delivering end-to-end AI/ML systems, from data preparation and model development to model deployment, feature stores, model management and monitoring model management Delivering solutions using the latest GenAI and Agentic Frameworks, such … Generative and Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ADK, or similar. Ability to design and implement RAG pipelines, agentic workflows, MCP and integration with LLM APIs (OpenAI, Anthropic, Hugging Face OR similar). Proficiency in CI/CD and containerisation: GitHub Actions, Azure DevOps, Docker, Kubernetes. ...

RBAC and Cost Controls. Software Engineering: Clean Code (SOLID, DRY), DDD, modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens. Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK. WHAT YOU'LL LOVE ...

gateway/Bedrock patterns, data residency, SSO/OIDC federation, and cost controls. Experience with Claude/Anthropic, OpenAI, Microsoft Copilot families, including MCP, connectors, skills, and trade‐offs. Strong understanding of AI testing disciplines (accuracy, hallucination, bias, prompt evaluations) and AI governance/risk (DPIA, data classification, FCA considerations ...

/Sub, Cloud Storage). Experience with an LLM observability or evaluation platform such as Langfuse, LangSmith, Braintrust or Arize Phoenix. Understanding of MCP and integration of tools with agentic systems. Experience grounding LLM output in data via techniques such as RAG Experience with an LLM orchestration or agent framework ...

from monolithic to microservice architectures Experience deploying or governing enterprise AI tooling (Claude Enterprise, Copilot, or similar), particularly around secure rollout, usage policies, and MCP integrations What We Offer Opportunity to shape and own the technical infrastructure Small, collaborative team environment where your expertise will have a direct impact Opportunity ...

vendor. Experience shipping software via marketplaces (Atlassian Marketplace, monday.com Apps, and similar). Hands‐on with agentic development tooling beyond chat (Claude Code, Cursor, MCP‐based workflows, and the like). Experience taking AI features to production at scale: evaluation, cost control, latency, safety. Why us? Backed by 20+ years ...

data grounding Architect reusable AI design patterns including human‐in‐the‐loop workflows and multi‐agent coordination models Apply agent integration and communication standards (MCP, A2A, OpenAPI, REST, gRPC) Lead technical delivery of AI projects, managing timelines, dependencies, and stakeholder expectations Ensure delivery adheres to AI governance, data privacy … model evaluation approaches Hands‐on experience with multi‐agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel) Familiarity with orchestration protocols such as MCP, A2A, and OpenAPI‐based integration Strong Python development skills and knowledge of CI/CD, DevOps, and cloud‐native architectures Practical experience with Azure (Azure OpenAI ...

Grid and Integration On-Premises and SaaS Thoughtful leadership in AI to incorporate more efficient ways of working using GenAI and Agentic Agents using MCP and A2A. Working knowledge and experience in Azure DevOps and CICD to deploy Azure Integration services Architectural knowledge with good understanding of Integration Patterns, Hybrid ...

LLMs for predictive insights and adaptive remediation. Experience architecting agentic infrastructures, including observability pipelines and experimentation frameworks for AI agents. Familiarity with MCP and A2A orchestration patterns running on Kubernetes, enabling agents to communicate through secure service meshes. Working knowledge of Agent Gateways and Registries, bridging microservices and AI agents ...

world datasets. IDE automation and AI tooling (Cursor, Claude, Copilot, Vertex, Gemini, etc.), LLM integrations applied to data and BigQuery, and Agentic AI/MCP experience. 25 days Annual Leave, plus 8 Bank Holidays (more holiday with service - up to an extra 5 days off per year based on your ...

Machine Learning projects through workshops and deep dives with stakeholders across various departments. Define the technical feasibility of proposed AI use cases, identifying appropriate model architectures (LLMs, SLMs, or traditional ML) and success metrics (Accuracy, F1-score, Perplexity, etc.). Analyze existing business processes to identify automation opportunities … Kubernetes). Experience working in an Agile/Scrum development environment. Knowledge of AI security frameworks and responsible AI practices (e.g., OWASP for LLMs, MCP). Industry experience in manufacturing or a related industrial sector. Physical Demands Duties of this position are performed in a normal office environment. Duties ...

guide and review AI‐generated code with confidence. Hands‐on experience building agentic systems using frameworks such as LangGraph, Microsoft Agentic Framework, or MCP, with a solid understanding of LLM capabilities and risks. Experience designing and running experiments to validate ideas quickly, using technical prototypes, customer feedback, and lean startup ...

lead developer embedded within customer accounts, for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters. Build ...

helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team … tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. Work across product and infrastructure: Partner with the team ...

polyglot codebase Fluent or willing to learn Go Hands-on experience building and operating production AI applications using LLMs and agentic frameworks (e.g., RAG, MCP, LangGraph or similar), including tool integration, prompt design, evaluation, guardrails, and token/cost optimization. Demonstrate ability to create reliable agents (prompting, evaluation, guardrails, understanding ...

/UDP , packet and latency path analysis, dedicated network infrastructure, and kernel bypass techniques ( DPDK ) Familiarity with agentic engineering tools and concepts: LLMs , MCP APIs , AI‐First IDEs (e.g. Cursor, Claude Code), harness engineering , and workflow automation Ability to make sound architectural decisions, articulate trade‐offs clearly, and guide implementation ...

oriented programming language (e.g., JavaScript/TypeScript, Python, Java, C#, etc.). AI & Next-Gen Tech: * Hands-on experience with GenAI (e.g., Playwright with MCP). Required experience with AI-assisted coding tools (e.g., GitHub Copilot, Claude). Knowledge of LangChain , LangGraph , or cloud environments is highly desirable (a plus ...

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. ...