2 of 2 Model Context Protocol Jobs in Leicestershire

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 ...