AI Technologist

Responsibilities

• Blueprint Generation: Following live sprints, co-author the replicable scaling playbook. Translate highly complex architectural decisions into accessible, step-by-step operational guides detailing execution parameters, security protocols, and necessary architectural guardrails for BAU teams.
• Training and Development: Develop and deliver training programs to educate MFG teams on AI concepts, tools, and best practices, fostering a culture of AI experimentation and learning within MFG APAC

Requirements

• 7 to 10 years of robust experience in enterprise technical architecture, cloud infrastructure provisioning, or highly technical product management.
• Deep understanding and hands-on experience with generative AI models, particularly Google Gemini, and a proven ability to leverage these capabilities for advertising-specific applications (e.g., content creation, campaign optimization, audience insights).
• Extensive practical experience integrating Foundational Large Language Models (LLMs) into enterprise workflows via APIs. Working knowledge of the broader AI ecosystem, including ChatGPT, Grok, Meta AI, and other relevant technologies.
• Demonstrated expertise in advanced prompt engineering and optimizing outputs for complex, multi-step advertising tasks.
• Demonstrable understanding of architectural design patterns and their specific application to artificial intelligence systems.
• Familiarity with data analysis and machine learning concepts as they specifically relate to deploying AI in digital advertising.
• Key Competencies
• Advanced Generative AI Fluency: Deep, operational understanding of how to apply existing foundational models to solve complex, real-world marketing problems without needing to build statistical ML models from scratch.
• Agentic Architecture: Expert ability to map complex systems, identify redundancies, and design secure, multi-agent workflows that can operate autonomously within enterprise guardrails.
• Process Engineering: Expert ability to map complex systems, identify redundancies, and design automated workflows.
• Systems Thinking: Advanced capacity to understand how disparate APIs, LLMs, and legacy tools interact within a live enterprise environment.
• Analytical Rigor: Meticulous approach to diagnosi

Additional Information

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 Technologist operates as the core technical architect in charge of the overarching infrastructure and workflow strategy. This role functions akin to an advanced software architect, specializing in the integration and application of pre-existing foundational generative models (such as Google Gemini) to construct comprehensive, end-to-end automated systems that serve immediate commercial purposes.

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