401 to 425 of 587 Permanent Model Context Protocol Jobs

through LLMs and NLP. Deploys LLM and agentic capabilities to improve engineering quality, delivery speed, and operational resilience, covering automated code review, standards enforcement, context‐aware development assistance, copilot‐delivered boilerplates, root‐cause analysis, incident diagnosis, and system audits that surface technical debt, delivering measurable reductions in rework … native vendors at various maturity stages. Familiarity with current AI industry developments, including agentic AI systems, emerging agent‐to‐agent integration standards (e.g., MCP), AI‐assisted software development (e.g., Claude Code, GitHub Copilot), frontier model capabilities, and evolving best practices for embedding AI into enterprise workflows. Experience working with ...

facing AI deployment. Deploy and integrate AI components built by our ML and Decisioning teams into production: the engineering implementation layer between a working model and a live customer feature. AI platform capabilities. Work with the AI Platforms team to turn engagement patterns into safe, increasingly self-serve company … integrate with both is required; existing expertise is a bonus rather than a requirement. Experience with agent hosting and sandboxing platforms, LLM or MCP gateways, or agentic workflow orchestration tooling. Experience in financial services or another regulated environment. Experience deploying models built by a data science team into customer-facing ...

Responsibilities Build production-grade GenAI, LLM, RAG and Agentic AI solutions Develop AI Agents and Multi-Agent Systems Work with LangChain, LangGraph and MCP Build intelligent retrieval using Embeddings, Vector Databases and Semantic Search Apply Prompt & Context Engineering Integrate AI solutions through REST APIs and cloud platforms Test, evaluate … Strong Python and SQL Hands-on experience with LLMs, RAG, AI Agents and Agentic AI Experience with LangChain and/or LangGraph Experience with MCP Knowledge of Embeddings and Vector Databases Experience deploying AI solutions in enterprise environments Cloud experience across Azure, AWS or GCP Understanding of LLM evaluation ...

solutions Guide decisions across low-code, pro-code, integration and AI patterns Design how AI agents use trusted knowledge, approved tools, MCP services, approvals, human hand-offs and safe failure paths Build evaluation, observability, identity, permissions and data boundaries into delivery Lead the design, build, test, deployment and support … using Power Apps, Power Automate, Dataverse, Copilot Studio and pro-code extensions Engineer AI agents and agentic workflows Design and implement integrations with approved MCP servers and develop MCP tools or services Integrate solutions with Microsoft 365, SharePoint, Microsoft Graph, Azure services and enterprise systems Apply grounding, retrieval-augmented generation ...

manage risk, non-functional requirements (NFRs), and technical debt. Agentic AI & Commerce Innovation: Design AWS-based agentic AI platforms (orchestration, RAG, memory, guardrails, and MCP). Establish reusable patterns and advise clients on emerging Agentic Commerce standards (ACP, AP2, A2A, and secure payment models). Client Engagement & Account Growth: Build … patterns and appropriate integration components). Agentic AI & Commerce: Strong understanding of building agentic AI platforms on AWS (e.g., Bedrock, orchestrations, RAG, gateways/MCP) and awareness of emerging Agentic Commerce concepts and standards (ACP, AP2, A2A). Software Engineering & API Design: Strong development background (ideally TypeScript/JavaScript) coupled ...

best practices in AI engineering. Use best practices (e.g., MLOps, AIOps) to improve products/services and processes related to AI. Optimise existing model serving and data pipelines to meet changing performance and security requirements. Hold requirements gathering sessions with business stakeholders and data science teams. Lead functional projects … powered development tools like GitHub Copilot or similar platforms (e.g., Kiro, Cursor) to enhance productivity and code generation. Knowledge of or experience with MCP to integrate LLMs with external data sources and tools. At JET, this is on the menu: Our teams forge connections internally and work with some ...

trigger network actions. Support deployment and operation of AI platforms such as Vertex AI or similar. Integrate with vector databases, graph APIs, data pipelines, MCP servers, and automation backends. Support Kubernetes-based deployment of automation services, agent services, APIs, and microservices. Implement infrastructure-as-code for platform environments and network … Open APIs. NETCONF/RESTCONF, gRPC, vendor APIs. API management and orchestration. Intent-to-configuration workflows. Data pipelines. Vector databases and graph APIs. MCP integration. Security frameworks and compliance controls. Observability and logging. Preferred Certifications Kubernetes CKA/CKAD. Terraform Associate. Red Hat Ansible certification. Google Cloud, AWS, or Azure ...

trigger network actions.* Support deployment and operation of AI platforms such as Vertex AI or similar.* Integrate with vector databases, graph APIs, data pipelines, MCP servers, and automation backends.* Support Kubernetes-based deployment of automation services, agent services, APIs, and microservices.* Implement infrastructure-as-code for platform environments and network … Open APIs.* NETCONF/RESTCONF, gRPC, vendor APIs.* API management and orchestration.* Intent-to-configuration workflows.* Data pipelines.* Vector databases and graph APIs.* MCP integration.* Security frameworks and compliance controls.* Observability and logging.**Preferred Certifications*** Kubernetes CKA/CKAD.* Terraform Associate.* Red Hat Ansible certification.* Google Cloud, AWS, or Azure ...

customer-facing, technically demanding, and genuinely novel — there is no playbook yet, and we're writing it in real time. We call our delivery model co-work. We don't build things for our customers. We build alongside them, teaching them to think, design, and ship with Claude … Scope engagements: assumptions, risks, milestones, and dependencies Embed with customer teams to co-build agentic applications on the Claude Build technical artifacts — evaluation frameworks, MCP servers, sub-agents, and deployment configurations — tailored to the customer's stack What Success Looks Like Customers move from proof-of-value to production Engineering ...

Bedrock, Docker). Notable understanding and experience building generative AI applications (LangChain, AutoGen, CrewAI or similar). Validated production experience with RAG, agent, and MCP-based systems, including AgentOps (CI/CD, monitoring, optimisation). Applied, pragmatic "builder/hacker" mindset with rapid iteration (idea to POC to production). … ongoing support for the continued effectiveness of analytics and modelling solutions to users. Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy. Ensure all development activities are undertaken within the defined control environment. Vice President Expectations To contribute or set strategy, drive requirements and make ...

manage risk, non-functional requirements (NFRs), and technical debt. Agentic AI & Commerce Innovation: Design AWS-based agentic AI platforms (orchestration, RAG, memory, guardrails, and MCP). Establish reusable patterns and advise clients on emerging Agentic Commerce standards (ACP, AP2, A2A, and secure payment models).Client Engagement & Account Growth: Build trusted … serverless patterns and appropriate integration components).Agentic AI & Commerce: Strong understanding of building agentic AI platforms on AWS (e.g., Bedrock, orchestrations, RAG, gateways/MCP) and awareness of emerging Agentic Commerce concepts and standards (ACP, AP2, A2A).Software Engineering & API Design: Strong development background (ideally TypeScript/JavaScript) coupled with ...

want to talk to you!* Understand Agent Interoperability - Map and integrate external agents from hyperscalers (e.g. Copilot, Gemini) into Agentforce via open standards (MCP, A2A); design how these systems collaborate.* Enable Conversational & Background Agents - Use Agentforce Studio and Agent Builder to configure chat and background agents; integrate with external channels … Agentforce and deep fluency with D360 and core Salesforce platform services.* Advanced Integration - Experience integrating Salesforce with external agents via APIs and open standards (MCP, A2A).* Governance & Observability - Familiarity with prompt governance, observability, and monitoring frameworks.* Cross-Platform Background - Background in cross-platform integrations (e.g., Hyperscaler SDKs to Salesforce ...

want to talk to you! Understand Agent Interoperability - Map and integrate external agents from hyperscalers (e.g. Copilot, Gemini) into Agentforce via open standards (MCP, A2A); design how these systems collaborate. Enable Conversational & Background Agents - Use Agentforce Studio and Agent Builder to configure chat and background agents; integrate with external channels … Agentforce and deep fluency with D360 and core Salesforce platform services. Advanced Integration - Experience integrating Salesforce with external agents via APIs and open standards (MCP, A2A). Governance & Observability - Familiarity with prompt governance, observability, and monitoring frameworks. Cross‐Platform Background - Background in cross‐platform integrations (e.g., Hyperscaler SDKs to Salesforce ...

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. ...

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 ...

production products and platforms. You will be an early member of our Industry & Enterprise FDE capability, working alongside senior FDEs to help shape the model, learn and apply repeatable patterns, and contribute to raising the bar for what enterprise AI deployment looks like in practice. What … workflows and processes ensuring solutions meet enterprise requirements for performance, security, and reliability. Develop technical assets — Create reusable, production-ready artefacts or tools including MCP servers, sub-agents, agent orchestration frameworks, and evaluation tooling that can be deployed across client workflows. Support enterprise deployments — Play a key technical role ...

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 ...