AI Enterprise Senior Technical Lead

Who We Are WPP Enterprise Solutions designs, builds, and operates the growth systems that competitive businesses rely on. In a world where Al is reshaping how companies drive growth, we lead clients in business transformation and marketing modernization, connecting strategy directly to execution. Our 12,000 experts in engineering and platforms, commerce, consulting, content transformation, CRM, and CX work within a unified global operating unit across 40+ markets. WPP Enterprise Solutions works alongside best-in-class partners including Adobe, AWS, Braze, Google, Microsoft, Salesforce, and Shopify, as well as innovators in AI, to deliver growth solutions tailored to the needs of our clients’ businesses. VML, part of WPP, supports WPP Enterprise Solutions by helping brands activate transformation through creativity and experience. The opportunity We are looking for an AI Enterprise Technical Lead to join a high-profile enterprise AI project for a major global brand. This is a high-impact technical leadership role combining ownership of enterprise AI delivery, client-facing discovery and technical workshops with strong architectural influence and a balance between technical leadership and hands-on engineering. You will help shape and deliver a secure, enterprise-grade AI platform built around Microsoft Azure, LLMs, agentic workflows, enterprise knowledge and integrations . A key part of the role is understanding AI as part of a larger enterprise architecture . You will make pragmatic decisions about where LLMs and agents add value, where deterministic software is the better choice, how enterprise knowledge should be retrieved and how AI capabilities should integrate with existing platforms. What you’ll get to do Lead technical discovery and solution design , translating business workflows into scalable AI solutions. Shape architecture across AI agents, orchestration, RAG/retrieval, Azure services and enterprise integrations . Define clear boundaries between AI/LLM capabilities and deterministic application logic . Design agent workflows, context management, tool usage and appropriate human-in-the-loop controls. Shape RAG and enterprise knowledge solutions , including retrieval and use of trusted sources. Design integrations between AI workflows, APIs and existing enterprise platforms. Ensure appropriate approaches to security, identity and access, governance, observability and auditability . Turn discovery outcomes into architecture, technical scope and an actionable implementation backlog. Lead engineers throughout delivery, providing hands-on guidance, code reviews and support with complex technical decisions. Establish effective approaches to AI evaluation, testing and continuous improvement . What you should have