AI Enterprise SeniorTechnical Lead

About this role

Who We Are VML is a global creative company that combines brand experience, customer experience, and commerce to create connected brands that drive growth. Guided by a Human First philosophy, VML is known for its innovative work for brands and consistently ranks among the world’s leading creative companies, including the WARC Creative 100. VML’s global network spans 55+ markets with principal offices in Buenos Aires, Kansas City, London, New York, São Paulo, Shanghai and Singapore.

VML is part of WPP, the trusted growth partner for the world's leading brands. Powered by exceptional talent and our agentic marketing platform WPP Open, WPP unites cutting-edge media intelligence and data solutions, creativity, production, enterprise solutions and expert strategic counsel. For more information, please visit www.vml.com and follow along on LinkedIn #WeAreVML. 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 .