8 of 8 Permanent Model Context Protocol Jobs in North Wales

admin position. A. Agentforce Architecture & System Design Solution Architecture: Translate complex enterprise business processes into end-to-end agentic workflows (Intent $\rightarrow$ Agent $\rightarrow$ Context $\rightarrow$ Reasoning $\rightarrow$ Actions $\rightarrow$ Systems $\rightarrow$ Outcome). Core Agent Engineering: Design, configure, and build enterprise agents using Agent Builder, Agentforce Studio, Agent … search, and Knowledge libraries. System Interoperability: Architect REST API callouts, event-driven integrations, and MuleSoft platform pipelines, incorporating Model Context Protocol (MCP) standards. D. Testing, Security & Strategic Advisory Testing & Quality Assurance: Drive automated testing and multi-turn conversation tracing using the Agentforce Testing Center. Security & Guardrails: Design ...

team and set the bar in design reviews and code reviews. Engage with the open source and agentic development community around sandboxing, MCP, and related ecosystems. Participate in on-call rotations and respond to critical stability issues affecting users. Document your work clearly and share knowledge with the rest ...

expand into agentic solution delivery and broader business transformation. Our conviction is that engineers are uniquely positioned to lead this transformation. The strongest mental model for designing, deploying, and governing AI agents in production lives in software engineering. The teams that change how their organization builds software … assumptions, risks, milestones, and dependencies Embed with customer teams to co-build agentic applications on the Claude developer platform 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 ...

expand into agentic solution delivery and broader business transformation. Our conviction is that engineers are uniquely positioned to lead this transformation. The strongest mental model for designing, deploying, and governing AI agents in production lives in software engineering. The teams that change how their organization builds software … assumptions, risks, milestones, and dependencies Embed with customer teams to co-build agentic applications on the Claude developer platform 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 ...

expand into agentic solution delivery and broader business transformation. Our conviction is that engineers are uniquely positioned to lead this transformation. The strongest mental model for designing, deploying, and governing AI agents in production lives in software engineering. The teams that change how their organization builds software … assumptions, risks, milestones, and dependencies Embed with customer teams to co-build agentic applications on the Claude developer platform 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 ...

build pipelines Software supply chain integrity Container security and governance AI/ML workload governance (where applicable) AI agent architecture patterns: isolated execution environments, MCP policy enforcement, model artifact provenance Partner with Sales Engineers and Post-Sales teams to ensure technical continuity without owning deal cycles. What … packaging, dependency management, reproducibility, and governance considerations within containerized environments. Practical Experience with AI coding agent runtimes and sandboxed execution environments (e.g., agent isolation, MCP tool governance) Familiarity with Docker SBX and MCP Gateway as enterprise controls for agentic AI workloads Familiarity with secure software supply chain practices, including SBOM ...

moving from a traditional SaaS posture to a platform built around agents - parent agents fronting our compensation data, specialist agents underneath, durable workflows, an MCP-based tool layer, and an eval harness to maintain consistency. You’ll own architecture and technical design across the stack: the customer-facing … have Production experience with agentic systems - tool calling, multi-step orchestration, LLM evals. Workflow engines (Temporal, Cadence, Step Functions) - even if not Temporal specifically MCP, Anthropic SDK, or other LLM platform work Building developer platforms, internal SDKs, or framework-shaped surfaces Eval-driven development, prompt engineering at scale, LLM-judge ...

agent can use?" before asking "does this data exist?". As that foundation takes shape, your scope expands naturally into Grip's MCP design, agentic workflows and AI system architecture. In your own workflow, agentic tooling is already the default. You use Claude Code, GitHub automations and agents to manage … Define success metrics and build feedback loops that keep product decisions grounded in data. Expanding into AI & agentic - as your scope grows Contribute to MCP tool design, shaping how Grip's data is exposed and consumed within agentic systems. Work with the Data and AI squad to identify where agentic ...