Infrastructure Lead

Key Responsibilities

• Own the infrastructure layer that connects intelligent agents securely to business systems.
• Manage MCP (Model Context Protocol) servers, system access controls, and environment connections.
• Support integrations with platforms including Microsoft 365, Airtable, SharePoint, and Sage.
• Guide orchestration activities to support AI agent deployments.
• Manage compute scaling requirements.
• Ensure model training goals are achieved efficiently.
• Maintain strict cost controls across AI infrastructure and environments.
• Build strong, scalable, and reliable environments that support rapid deployment.
• Ensure the secure and governed connection of AI agents into core enterprise platforms.
• Ensure appropriate access controls and permissions are in place as agentic systems interact with live business data.

Skills, Knowledge & Expertise

• Experience managing large-scale containerised applications using Kubernetes.
• Strong knowledge and experience of cloud architecture, specifically Azure.
• Confidence deploying Infrastructure as Code using tools such as Terraform.
• Strong understanding of GPU provisioning.
• Experience building and operating in data-heavy environments, ideally with exposure to machine learning or AI infrastructure.
• Practical experience with MCP (Model Context Protocol) servers, or comparable agent orchestration and tool integration frameworks used to connect AI agents to enterprise systems.
• Understanding of system access controls, identity management, and permissions management, particularly in governing AI agent access to sensitive business systems and data.
• Comfortable working with IT Infrastructure teams to align AI infrastructure decisions with broader technology, security, and compliance standards.
• Strong communication skills, with the ability to engage effectively with both specialist technical teams and business users.
• Experience working in a fast-paced change environment.

Benefits