Director, AI Solutions Engineer

About WPP Media  

WPP is the trusted growth partner for the world’s leading brands. With exceptional talent, trusted data and intelligence, and world-class partnerships – all united by our pioneering agentic marketing platform, WPP Open – we help clients navigate change, capture opportunity, and deliver transformational growth.   

WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working.  

For more information, visit wppmedia.com. 

 Role Summary and Impact 

 

The Media Futures Group AI Squad is a small, agile, and autonomous innovation team dedicated to charting the course for AI transformation across APAC for one of WPP’s most important and strategic global technology clients. 
 
By seamlessly integrating AI across media, creative, and production, this cross-functional squad delivers cutting-edge innovation and pioneering work to deliver more effective and efficient business outcomes. 
 
The team’s mission is to solve specific business challenges by delivering demonstrable proof of AI-enabled marketing improvements, providing strategic guideposts for the broader organization. 
 
Utilizing best-in-class tools like WPP Open and Gemini, you will innovate and deliver award-winning creative ideas while building, testing, and scaling solutions that enhance effectiveness, efficiency, and execution for our clients. 

 

 The AI Solutions Engineer serves as the master builder executing the construction. This highly technical role provides the dedicated, hands-on development support required to forcefully move theoretical architectural visions out of isolated testing environments and into highly secure, Google-approved, enterprise-grade production infrastructures. The AI Solutions Engineer bridges the critical, often perilous gap between a fragile, locally hosted prototype and a highly scalable, robust organizational tool capable of withstanding massive global traffic. 

Responsibilities 

• API & UI Development: Construct complex backend Application Programming Interface (API) connections and develop the secure user interfaces absolutely necessary to bridge the proprietary WPP Open platform with localized campaign tools and highly guarded client data lakes. 

• Live Deployment & Debugging: Execute rapid debugging, performance analysis, and troubleshooting of both machine learning models and underlying cloud infrastructure in real-time to prevent catastrophic performance degradation or service outages during live campaign sprints. 

• Security & Compliance: Strictly document the deployed technical architecture upon the conclusion of active campaigns. Solidify security protocols and data pipelines to ensure absolute compliance with enterprise risk standards and global data privacy regulations. 

• Codebase Handover: Facilitate the seamless handover of the finalized codebase to centralized, operations-driven technology teams, ensuring pristine code quality, proper containerization, and long-term deployment readiness. 

Skills and Experience 

• A minimum of 5 years of applied experience in software engineering, highly technical support, or complex solutions engineering. 

• At least 2 years focused exclusively on deploying machine learning (ML) or natural language processing (NLP) applications in live commercial environments. 

• Exceptional coding and scripting capabilities, primarily utilizing Python, Java, C++, or Go. 

• Deep, academic understanding of data structures, complex algorithms, and object-oriented software design principles. 

• Proven, hands-on experience troubleshooting, debugging, and reproducing obscure issues within advanced machine learning frameworks, specifically TensorFlow, Keras, and PyTorch. 

• Extensive operational experience navigating public cloud services, specifically Google Cloud Platform (GCP) components such as Kubernetes, Compute Engine, and Apache Beam. 

• Thorough understanding of computer networking, peering with private clouds, managing highly distributed systems, and Git version control. 

Key Competencies 

• Vertex MLOps & Cloud Infrastructure Deployment: Capable of establishing robust, automated machine learning pipelines using Vertex AI Pipelines and Google Cloud Platform components like Kubernetes and Compute Engine. Must ensure that generative AI tools are properly containerized to scale securely and withstand massive global traffic during live campaigns. 

• Vertex AI Mastery: Deep, hands-on proficiency with Google Cloud's Vertex AI platform as the exclusive, mandated environment for model deployment. Capable of navigating the Vertex Model Garden, configuring foundational models (like Gemini), and executing parameter-efficient fine-tuning for specific campaign needs 

• Secure RAG & Grounding Pipeline Engineering: Expert ability to build complex Retrieval-Augmented Generation (RAG) architectures within Vertex AI. Must demonstrate high technical acumen in securely connecting generative models to highly guarded, proprietary enterprise data lakes and Customer Data Platforms without exposing PII or violating data governance. 

• Rapid Problem-Solving: Ability to diagnose and repair code-level pipeline failures or UI breakdowns under the extreme pressure of a live campaign sprint.