401 to 425 of 573 Model Context Protocol Jobs

secure and governed access patterns for LLMs and enterprise tools using APIM, platform gateways, Entra ID, RBAC and managed identities Contribute to LLMOps and model runtime patterns, including model access, routing, caching, token optimisation … cost-aware usage controls Support lifecycle and evaluation practices for agent configurations, prompts and AI workflows Design secure tool-access patterns for agents, including MCP/tool abstraction, credential management and enterprise API integration Contribute to AgentOps and GenAIOps capabilities, including telemetry, run history, task outcomes, error analysis and feedback ...

join a small, high-leverage team building production infrastructure for Generative AI at Deliveroo and DoorDash, with a primary focus on our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You'll work across model … gateways, model routing, vendor abstraction, or cost attributionExperience building developer platforms, internal platforms, or self-serve infrastructureExperience building and deploying AI agents or MCP servers in productionExperience with eval systems, LLM observability, tracing, RAG, search, or vector databasesDiversity, Equity and InclusionAt Deliveroo, we know that a great workplace reflects ...

becoming the primary way people interact with Zopa. Underneath it sits a platform we have built ourselves: an agentic loop, MCP-based tools, memory, a generic front end and an evals framework. Because that platform exists, the work has changed shape. A new customer experience is often a prompt change ...

make Entropia the room they reach for on the next mandate. This role is based in London. We mainly use an in-person work model, with a flexible work-from-home policy. Strategic Implementation: Take the lead in integrating Entropia's solutions into client workflows, ensuring smooth adoption ...

directly with trading desks, providing a rare and exciting opportunity to gain direct front‐office exposure. You’ll work at the intersection of business context and applied AI: understanding how teams operate, then helping them adopt approved AI tools safely and effectively through training, workflow mapping, and lightweight prototyping. … interaction, including: Practical understanding of prompt engineering techniques and common LLM failure modes Experience grounding AI outputs in data (e.g. through document retrieval, APIs, MCP or structured context rather than free‐text prompting alone) Exposure to designing AI‐assisted workflows that support repeatable tasks rather than one‐off interactions. ...

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 ...

other systems of record and engagement. Design integration patterns that let AI capabilities interoperate safely with enterprise data, identity,workflowand process automation platforms– including MCP and A2A and how these capabilities enable an enterprise Agent mesh. Understand the data,governanceand change implications of embedding AI into mission-critical enterprise processes. … Orchestration & control plane Architect the orchestration and control-plane layer that governs how AI capabilities are exposed,routedand managed across the enterprise. Design MCP, AI and LLM gateway layers for secure,observableand policy-controlled access to models and tools. Design agent and skills registries — including recommending suitable technologies and patterns ...

across human users, systems, and non-human agents. Our Tech & Ecosystem: Databricks, Lakebase, Unity Catalog, Entra ID/Azure Identity, Okta, ZScaler, GitHub Actions, MCP patterns, and Terraform What you'll do Platform Engineering & CI/CD Build and maintain Infrastructure-as-Code (IaC) using Terraform across development, test … deprovisioning and access models with single-revoke capability and full auditability. AI Gateway & Governance Harden existing AI gateway and agent orchestration layers (built on MCP patterns) into secure, production-ready capabilities. Implement API gateway controls: authentication, routing, rate limiting, token budgets, policy-as-code, and action logging. Build platform-, tool ...

batch patterns, data graph design, and activation strategies within D360.Map and integrate external agents from hyperscalers (e.g., Copilot, Gemini) into Agentforce via open standards (MCP, A2A); advise customers on how these systems collaborate within their enterprise architecture.Navigate ambiguous, high-stakes technical conversations with authority — knowing when to prescribe, when … engineering, agent lifecycle management, and hands-on prototype development.Hands-on proficiency in programming (e.g., Python, JavaScript, SQL) and data frameworks.Understanding of agent interoperability standards (MCP, A2A) and the broader external agent ecosystem.Experience operating in complex, matrixed enterprise environments across multiple EMEA markets.Exceptional communicator and storyteller — able to translate architectural complexity ...

intelligent search) Familiarity with Retrieval-Augmented Generation (RAG), vector databases, or embeddings Experience with cloud platforms (AWS preferred) Awareness of emerging AI tooling (e.g. MCP, A2A, Threads or similar) Open-source contributions or side projects, particularly involving scalable systems or AI This role is best suited to software engineers … interested in applying AI to enhance real-world products and platforms. What's in it for me? Salary £70,000 - £100,000 Hybrid working model with remote flexibility Private healthcare Professional development and funded learning Opportunity to work on modern, AI-enabled systems at scale Clear progression within ...

used by institutional clients. As an early member of a small, senior team, you will work end‐to‐end across research, prototyping, data engineering, model implementation, production systems, and client‐facing applications. This is a high‐ownership role for someone who is comfortable contributing wherever needed in a fast … help harden new modelling approaches, analytical tools, and platform features. Work across the design and build of our internal AI layer, including LLM integrations, MCP servers, and agentic tooling, to automate research workflows and deliver analytical insights within the client‐facing platform. Help with the evolution of our cloud infrastructure ...

that analytics is embedded in day‐to‐day decision‐making rather than delivered as isolated reports. The role holder will apply and role‐model the technical standards the team works to peer review, version control, documentation, testing and release management -and will aid the Data Analytics Manager to raise … with Data Scientists and Actuarial. Hands‐on experience applying AI/LLM tooling to analytics work (e.g. Co‐pilot for Power BI/Fabric, MCP‐style integrations, agentic assistants, code‐generation tools) with a pragmatic view on where they add value. Experience with Microsoft Fabric, dbt, Azure DevOps/GitHub ...

functionality directly into software products Working with technologies such as OpenAI, Azure OpenAI, Claude, Gemini or local models Exploring RAG, AI agents, Semantic Kernel, MCP, vector search and intelligent workflows Engineering around the realities of production AI: accuracy, security, validation, guardrails, latency and cost Working across the stack, including modern … code. That experience could be commercial, independent or through substantial personal projects what matters is that you can explain what you built, how the model was integrated and the engineering decisions surrounding it. Why consider it? This is an opportunity to join a substantial software organisation at a point ...

functionality directly into software products Working with technologies such as OpenAI, Azure OpenAI, Claude, Gemini or local models Exploring RAG, AI agents, Semantic Kernel, MCP, vector search and intelligent workflows Engineering around the realities of production AI: accuracy, security, validation, guardrails, latency and cost Working across the stack, including modern … code. That experience could be commercial, independent or through substantial personal projects what matters is that you can explain what you built, how the model was integrated and the engineering decisions surrounding it. Why consider it? This is an opportunity to join a substantial software organisation at a point ...

functionality directly into software products Working with technologies such as OpenAI, Azure OpenAI, Claude, Gemini or local models Exploring RAG, AI agents, Semantic Kernel, MCP, vector search and intelligent workflows Engineering around the realities of production AI: accuracy, security, validation, guardrails, latency and cost Working across the stack, including modern … code. That experience could be commercial, independent or through substantial personal projects what matters is that you can explain what you built, how the model was integrated and the engineering decisions surrounding it. Why consider it? This is an opportunity to join a substantial software organisation at a point ...

solve real, complex business problems. Owning delivery end-to-end - from initial exploration through to production deployment, integration and ongoing iteration. Working with MCP-style architectures (FastMCP/FastAPI) and LangChain/LangGraph or equivalent frameworks to build reliable, scalable systems. Integrating AI into products, APIs and core business workflows … principles. Cloud deployment experience across AWS, GCP or Azure, using modern engineering practices. A product mindset - you care about impact and adoption, not just model performance. You understand LLM and machine learning trade-offs and design systems accordingly. About you: You'll likely have a Masters or higher ...

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. As a Software Engineer on the AI team you will build systems where LLMs autonomously plan, and call tools, to navigate … 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 ...

maintaining human-in-the-loop systems and AI monitoring/observability Strong fundamentals in AI/ML evaluation frameworks Experience building agentic systems including MCP, tool calling, memory systems, vector-based knowledge stores, guardrails In depth understanding of modern software design principles (e,g. microservices, event-driven architectures, domain driven … Management is a plus Key Responsibilities Develop and maintain Python-based AI applications Build and maintain document workflows using LLMs and classical NLP Debug model performance issues, handle edge cases, and optimize system reliability Write comprehensive tests and implement monitoring for AI/ML systems Example projects you might ...

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 … create and implement new user experiences Adapt proof-of-concept solutions into production-ready, scalable implementations Leverage AI, machine learning, and large language model technologies to develop innovative platform features Investigate, diagnose, and resolve technical issues to maintain commercially viable solutionsContribute to API design decisions, understanding considerations and trade ...

real-time/streaming interfaces, or data visualization. FastAPI and Pydantic experience. DynamoDB or Postgres, SQLAlchemy. Exposure to LLM application development, agent frameworks, MCP, or building developer tools. Prior ops or on-call experience. Experience with distributed systems, async task processing, or observability tooling (tracing, metrics, logging). Our Offer … transform into AI-native organizations that are increasingly powered by autonomous agents. With our modular Agentic Decision Platform, customers combine AI agents, rules, relevant context, and human oversight to safely automate and optimize their decisions—approving more customers, reimbursing claims instantly, stopping fraud before it spreads, and financing every ...

someone who has successfully implemented automation and AI within a Security Operations environment and can articulate both the technical implementation and the operating model required for long-term success. Key Responsibilities Security Automation: * Design, develop and maintain security automation workflows using hyper-automation platforms such as Torq, Tines, Swimlane … measure AI effectiveness, accuracy, quality and operational benefit. * Ensure AI capabilities complement analysts rather than simply replace human activities. * Help define the future operating model for analysts working alongside AI agents and automation platforms. SOC Strategy and Transformation: * Develop a roadmap for Security Automation and AI adoption within ...

Desirable Experience with technologies such as Kafka, Kinesis, PostgreSQL or DynamoDB Practical experience using AI development tools Cursor, GitHub Copilot, Claude Code, LLM APIs, MCP-based tooling or agentic workflows to meaningfully accelerate real engineering work Experience building AI-assisted internal tooling, automations or agentic systems, or working with … Desirable Experience with technologies such as Kafka, Kinesis, PostgreSQL or DynamoDB Practical experience using AI development tools Cursor, GitHub Copilot, Claude Code, LLM APIs, MCP-based tooling or agentic workflows to meaningfully accelerate real engineering work Experience building AI-assisted internal tooling, automations or agentic systems, or working with ...

Engineer. The work spans the full stack of what engineering needs to do around a GenAI platform: solving problems natively, backend plumbing, API integrations, MCP server builds, and data connections. Working in our GenAI platform doesn't always mean writing code. Often it means applying engineering judgement to solve problems … develop along the way. Across both levels familiarity with Azure and Microsoft 365 is an advantage. Hands-on experience with LLM integration patterns, MCP tooling, and AI-enabled or agentic development environments is genuinely valued. AI and LLM experience - you're comfortable using GenAI tools such as Copilot, Claude ...

Engineer. The work spans the full stack of what engineering needs to do around a GenAI platform: solving problems natively, backend plumbing, API integrations, MCP server builds, and data connections. Working in our GenAI platform doesn't always mean writing code. Often it means applying engineering judgement to solve problems … develop along the way. Across both levels familiarity with Azure and Microsoft 365 is an advantage. Hands-on experience with LLM integration patterns, MCP tooling, and AI-enabled or agentic development environments is genuinely valued. AI and LLM experience - you're comfortable using GenAI tools such as Copilot, Claude ...

Engineer. The work spans the full stack of what engineering needs to do around a GenAI platform: solving problems natively, backend plumbing, API integrations, MCP server builds, and data connections. Working in our GenAI platform doesn't always mean writing code. Often it means applying engineering judgement to solve problems … develop along the way. Across both levels familiarity with Azure and Microsoft 365 is an advantage. Hands-on experience with LLM integration patterns, MCP tooling, and AI-enabled or agentic development environments is genuinely valued. AI and LLM experience - you're comfortable using GenAI tools such as Copilot, Claude ...