Integration Engineering Manager

Job Summary Be part of a fast-growing, innovative company pioneering “Liveable Technology” to transform diabetes care. We’re hiring a MuleSoft Integration Manager – AI Enablement to lead the integration capability that enables secure, governed, and scalable enterprise AI adoption.&#xa;&#xa; This role will be based in the United Kingdom and will partner closely with global technology, product, data, security, and business teams to make enterprise systems, APIs, and data safely available to AI agents, automation platforms, and intelligent business workflows. This capability is responsible for advancing Insulet’s AI enablement foundation through MuleSoft Anypoint Platform, MuleSoft AI Gateway, Model Context Protocol (MCP), MuleSoft Agent Fabric, API-led connectivity, event-driven integration, and secure agent-to-system orchestration . The role will help transform existing enterprise APIs and integrations into trusted, reusable, agent-ready assets that support automation, productivity, customer experience, and operational intelligence. As a member of the Integration leadership team, this manager will own the AI Enablement Integration portfolio , lead a globally distributed MuleSoft engineering team, and partner with Enterprise Architecture, AI/ML, Salesforce, Data, Security, Product, and Platform teams to design and operate the integration layer for the agentic enterprise in a highly regulated healthcare environment . Global AI Enablement & Collaboration Model Serve as a primary integration leader for enterprise AI enablement across the UK, EMEA, U.S., and global markets . Partner with AI, Salesforce, Data, Product, Security, Enterprise Architecture, SRE, and MuleSoft CoE teams to establish reusable agent-ready integration patterns. Enable secure access to enterprise systems and APIs through MCP servers, AI Gateway policies, governed API products, and reusable integration services . Support global delivery and follow-the-sun operational readiness for business-critical AI-enabled workflows. Act as a bridge between business ambition and technical execution, helping teams move from AI pilots to governed, production-grade AI capabilities. AI Enablement Capability Ownership This role owns the end-to-end integration capability that enables enterprise AI agents, copilots, automation platforms, and intelligent workflows to securely discover, access, and act on enterprise systems and data. MuleSoft AI Gateway and secure AI traffic management Model Context Protocol (MCP) enablement for enterprise APIs and tools MuleSoft Agent Fabric adoption, including tool discovery, agent governance, and agent-to-system orchestration Agent-ready API products, reusable integration assets, and governed API catalogs AI-enabled integration patterns across Salesforce, Data, ERP, customer, operational, and platform domains Observability, policy enforcement, auditability, and compliance for AI-driven integration flows The manager will oversee a broad portfolio of APIs, connectors, MCP-enabled tools, and integration services, ensuring that AI agents and automation platforms can interact with enterprise systems in a way that is secure, observable, reusable, scalable, and compliant . Key Responsibilities AI Enablement Leadership & Strategy Own the AI Enablement Integration roadmap , aligning MuleSoft capabilities with enterprise AI strategy, business priorities, and platform governance. Define how MuleSoft, APIs, MCP, AI Gateway, and Agent Fabric enable secure, reusable, and governed AI adoption across the enterprise. Partner with Product, Data, Salesforce, Security, and Architecture leaders to translate AI use cases into scalable integration capabilities. Drive adoption of API-led connectivity, Domain-Driven Design, agent-ready API design, and composable integration patterns . Balance innovation, speed-to-value, security, compliance, operational resilience, and long-term platform sustainability. Agentic I ntegration Delivery & Design Oversight Oversee design and implementation of System, Process, Experience, and Agent-ready APIs that expose enterprise capabilities safely to AI agents and automation platforms. Lead implementation patterns for MCP servers, tool registration, agent action enablement, AI Gateway routing, policy enforcement, and agent-to-system orchestration . Ensure AI-enabled integrations follow strong standards for identity, consent, access control, data minimisation , rate limiting, observability, and auditability. Provide <span