451 to 475 of 590 Permanent Model Context Protocol Jobs

automation Hands-on experience with Claude Code (or equivalent agentic CLI tooling — Cursor, Codex CLI, Cline, Aider): writing custom skills, building subagent systems, implementing MCP servers, and authoring AGENTS.md/CLAUDE.md context files Platform-as-a-product mindset: builds reusable assets with their consumers in mind, prioritises discoverability … infrastructure patterns that form the core of the central platform’s offering Develop Claude Code (or equivalent agentic CLI tooling) skills, subagents, and MCP servers that become the standard AI tooling distributed to all client teams Implement golden path templates — project scaffolding, pipeline configuration, security guardrails, AI-native workflow defaults ...

teams and SaaS platforms, with autonomy supported by a US-based CEO and GTM. You will conduct live product demos, speak credibly about APIs, MCP, and integration architecture. #J-18808-Ljbffr ...

Experience architecting the data layer behind AI or analytics products in production. Informed views on the trade‐offs between fine‐tuning, RAG, and long‐context approaches, and how each changes data architecture … requirements, including context window economics and prompt caching. Familiarity with infrastructure as code, CI/CD, and observability for data platforms. Awareness of MCP and tool‐orchestration concepts and their implications for composable, data‐driven AI systems. Fluent use of AI‐assisted development tools (e.g. Claude Code, Cursor), with ...

tool, built while the value case is made * Delivering client POCs and MVPs: RAG pipelines, agent architectures, LLM integrations and protocol-driven tooling (MCP, tool orchestration) * Iterating in short loops: demoing every few days, taking feedback, changing course without ceremony * Engineering for production from day one: guardrails, security … data engineering to build the whole thing yourself * Hands-on production LLM and agent experience: prompt engineering, agent workflows, RAG, tool orchestration and MCP - with evidence you've shipped AI users actually rely on, and how you proved it could be trusted * Evaluation-driven habits: golden datasets, eval frameworks, guardrails ...

experience with AI Development Life Cycle practices and methodology. Orchestration: Production, hands-on experience with an agentic framework such as LangGraph, plus familiarity with MCP-based tool orchestration. Exposure to AutoGen, LlamaIndex, or CrewAI is a plus. Production Python engineering: Clean, modular, testable, maintainable code — you care about system reliability … much as model output. Evaluation & observability: Practical experience instrumenting tracing (LangSmith, Arize) and building CI/CD pipelines built specifically for LLMs. Engineering foundations: Distributed systems, scalable data pipelines (Kafka, SQL), and cloud-native infrastructure. Cloud-native deployment: Deep familiarity with shipping agentic workloads into production environments, ideally leveraging ...

experience with AI Development Life Cycle practices and methodology. Orchestration : Production, hands-on experience with an agentic framework such as LangGraph, plus familiarity with MCP-based tool orchestration. Exposure to AutoGen, LlamaIndex, or CrewAI is a plus. Production Python engineering : Clean, modular, testable, maintainable code — you care about system reliability … much as model output. Evaluation & observability : Practical experience instrumenting tracing (LangSmith, Arize) and building CI/CD pipelines built specifically for LLMs. Engineering foundations : Distributed systems, scalable data pipelines (Kafka, SQL), and cloud-native infrastructure. Cloud-native deployment: Deep familiarity with shipping agentic workloads into production environments, ideally leveraging ...

experience with AI Development Life Cycle practices and methodology. Orchestration : Production, hands‐on experience with an agentic framework such as LangGraph, plus familiarity with MCP‐based tool orchestration. Exposure to AutoGen, LlamaIndex, or CrewAI is a plus. Production Python engineering : Clean, modular, testable, maintainable code — you care about system reliability … much as model output. Evaluation & observability : Practical experience instrumenting tracing (LangSmith, Arize) and building CI/CD pipelines built specifically for LLMs. Engineering foundations : Distributed systems, scalable data pipelines (Kafka, SQL), and cloud‐native infrastructure. Cloud‐native deployment: Deep familiarity with shipping agentic workloads into production environments, ideally leveraging ...

work directly with client engineers and stakeholders, as an AI specialist. What you will be doing Building and shipping LLM-backed agents: tool use, MCP servers, retrieval, orchestration between specialist agents, evaluation and guardrails Working across cloud model APIs and locally hosted models, and making sensible calls about which … have not done one, we will support you through it Background in financial services, market data or another regulated, data-heavy domain Experience with MCP server development Experience with time series or analytical databases (kdb+/KDB-X, ClickHouse, Oracle) Python, Java and TypeScript Experience deploying models on-premise ...

Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling) Experience running AI systems in production at scale, including observability, cost and capacity planning, regression detection … Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling) Experience running AI systems in production at scale, including observability, cost and capacity planning, regression detection ...

with the modern LLM/agent toolkit — model APIs, prompting, tool use, RAG, and the patterns this fast‐moving ecosystem is converging on (MCP, agent frameworks, evals). You enjoy working closely with non‐engineers — you are the kind of person who'll sit with a scientist to understand … sustainable work-life balance and we are open to discussing flexible working arrangements. We are a hybrid team operating on a highly collaborative model that values synchronization and pair programming. You will be welcomed by a team of colleagues with decades of accumulated experience in their areas of expertise ...

with the modern LLM/agent toolkit - model APIs, prompting, tool use, RAG, and the patterns this fast-moving ecosystem is converging on (MCP, agent frameworks, evals). You enjoy working closely with non-engineers - you are the kind of person who'll sit with a scientist to understand … sustainable work-life balance and we are open to discussing flexible working arrangements. We are a hybrid team operating on a highly collaborative model that values synchronization and pair programming. You will be welcomed by a team of colleagues with decades of accumulated experience in their areas of expertise ...

review steadily upward. Pipeline Engineering Build and maintain the agentic pipeline: agent harness, blueprint engine interleaving deterministic steps (lint, build, git) with AI reasoning, MCP tool layer exposing internal APIs, warm sandbox pool, and retrieval over the codebase, tickets, and historical PRs. Own the economics of the pipeline: observability over … agent-proposed solution meets performance, scalability, and reliability requirements, and challenging designs that will not hold up under real workloads. Experience building agent infrastructure: MCP servers and tool layers, sandboxed execution, and CI/CD adapted for agent-driven workflows. Deep enough .NET/C# and SQL reading fluency ...

review steadily upward. Pipeline Engineering Build and maintain the agentic pipeline: agent harness, blueprint engine interleaving deterministic steps (lint, build, git) with AI reasoning, MCP tool layer exposing internal APIs, warm sandbox pool, and retrieval over the codebase, tickets, and historical PRs. Own the economics of the pipeline: observability over … agent-proposed solution meets performance, scalability, and reliability requirements, and challenging designs that will not hold up under real workloads. Experience building agent infrastructure: MCP servers and tool layers, sandboxed execution, and CI/CD adapted for agent-driven workflows. Deep enough .NET/C# and SQL reading fluency ...

design decisions, and assess technical risk Deep expertise in enterprise AI applications built on large language models, including agents, retrieval augmented generation, orchestration frameworks, model optimization, and evaluation frameworks … Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling) Experience running AI systems in production at scale, including observability, cost and capacity planning, regression detection ...

design decisions, and assess technical risk Deep expertise in enterprise AI applications built on large language models, including agents, retrieval augmented generation, orchestration frameworks, model optimization, and evaluation frameworks … Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling) Experience running AI systems in production at scale, including observability, cost and capacity planning, regression detection ...

zero. Based in Oxford, you will work in a dynamic and growing engineering organisation that builds cloud-based software to track and model power grids around the world. Please note that we are open to considering candidates who require visa sponsorship (subject to eligibility and company approval). Department … infrastructure Desirable attributes Hands-on experience building LLM-based systems Experience testing non-deterministic systems Understanding of statistics and inferential methods LangGraph, RAG, MCP, MLOps, IaaC, AWS What we offer Some of the benefits we include are: Private Medical Insurance Dental Insurance Parental Support Salary-Exchange Pension Employee Assistance Programme ...

frontier of how AI-augmented engineering works in practice — pioneering workflows using Claude Code, Claude MPM, and Duetto's in-house MCP server platform across US and European engineering teams. What Makes Us Different? Duetto is the hospitality industry's leading revenue management platform, founded in 2012 by former Wynn … OpenTelemetry, Datadog, Prometheus, Grafana, and Sentry instrumentation. You'll pioneer AI-augmented engineering workflows using Claude Code, Claude MPM, and Duetto's in-house MCP server platform (82+ tools) — setting the standard for how AI-assisted development works across US and European engineering teams. You'll drive architecture decisions through ...

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 … analysis, auto-triage of build/test failures).Establish policies and guardrails for AI usage in internal tools: data handling, prompt/response logging, model/provider selection, evaluation, fallback behaviors, and abuse prevention.Dev Productivity & Enterprise Tooling (Global Scale)Set technical direction and standards for the globally used developer ...

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 … analysis, auto-triage of build/test failures).Establish policies and guardrails for AI usage in internal tools: data handling, prompt/response logging, model/provider selection, evaluation, fallback behaviors, and abuse prevention.Dev Productivity & Enterprise Tooling (Global Scale)Set technical direction and standards for the globally used developer ...

innovation, and deliver better results across the company. You already have 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 these tools made you measurably faster. You know how to drive an agent … degree in Computer Science, Computer Engineering, or equivalent practical experience Demonstrated fluency across the agentic engineering toolchain — coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agentic frameworks — and can describe projects where these tools made you measurably faster Ability to drive an agent, validate its output ...

develop AI‐related features such as: Intelligent search/retrieval experiences and RAG Summarisation and document comprehension at scale Context management AI agents, MCP servers, and best‐practice configuration of, for example, AGENTS.md Advanced use of tools such as Claude Code and Codex Assistants and copilots embedded into workflows ...

governance, administration, security, and enablement features that internal teams require to build and run AI agents and workloads at scale — spanning our LLM Gateway, MCP Gateway, agent runtime, and model governance controls. This role requires strong technical judgment, a deep understanding of enterprise deployment patterns, and the ability … elegant, self-service product experiences for builders across the firm. Key Responsibilities Own the roadmap for core platform capabilities including the LLM and tool (MCP) gateways, web search access, audit logging, access controls, and integration of approved AWS and Azure AI services. Develop and maintain the builder experience ...

integrate pharmaceutical intelligence directly into their systems, workflows and AI environments. DDS delivers data via REST API, Snowflake, CRM integration, file transfer and MCP, serving clients from global pharma companies to emerging biotech and CDMOs. As AI-native data consumption grows, DDS is central to GlobalData’s strategy to evolve … sales Act as the technical lead in client meetings, running discovery and translating what you hear into a concrete solution across APIs, MCP, Snowflake and CRM delivery. Lead MCP pilots through to production, producing the integration guidance and solution documentation clients need. Answer the hard questions about our data honestly ...

Large Language Model (LLM) Technology Lead/Principal Architect Career Level: Manager/Senior Manager/Associate Director As a Lead or Principal AI Architect, you will serve as the definitive technical authority on AI architecture within client engagements and across the practice. You will own the complete …/IAP binding, and defense-in-depth enforcement Define the layered guardrail framework applied at every boundary, balancing protection with performance Govern the MCP control plane - registry, gateway, and risk scoring - across all internal and third-party servers Mandate adopt-over-build for productized evaluation and observability stacks Establish FinOps ...

agent sessions, and review outcomes critically before they ship. Build and maintain the team’s agentic tooling: custom Claude Code skills and sub-agents, MCP tools exposing internal APIs, prompt/context conventions (CLAUDE.md), and automated review pipelines. Design the verification that makes agent speed safe: test strategy, quality … communication: design docs, specifications, PR descriptions, and commit history that both humans and agents can act on. Bonus points if you have Experience building MCP servers or exposing internal APIs as agent-callable tools. Experience with LLM evaluation: eval suites, behavioural test design, or benchmarking agent workflows. Functional programming ...