AI Engineering Lead

Job Description:

Lead the AI Engineering capability for dentsu Media UK&I, identifying, shaping and building practical AI solutions that improve how Media teams work, deliver for clients and create measurable business value.

Working closely with Media leadership, Programme Leadership, Change Experience, Product, Data & Technology, Marketing Science and operational teams, this role will translate business problems into scalable AI-enabled solutions - moving ideas from opportunity identification through prototyping, engineering, testing, adoption and continuous improvement.

The role is accountable for building a small, high-impact AI engineering capability that can work with business teams to identify use cases, assess feasibility, design solutions, guide build activity, and ensure AI tools are embedded safely, effectively and sustainably into Media workflows. The ambition is to move from fragmented experimentation to a repeatable AI delivery model that creates value across planning, activation, operations, reporting, optimisation, workflow automation and client-facing services.

Lead the AI Engineering capability for dentsu Media UK&I, identifying, shaping and building practical AI solutions that improve how Media teams work, deliver for clients and create measurable business value.

Working closely with Media leadership, Programme Leadership, Change Experience, Product, Data & Technology, Marketing Science and operational teams, this role will translate business problems into scalable AI-enabled solutions - moving ideas from opportunity identification through prototyping, engineering, testing, adoption and continuous improvement.

The role is accountable for building a small, high-impact AI engineering capability that can work with business teams to identify use cases, assess feasibility, design solutions, guide build activity, and ensure AI tools are embedded safely, effectively and sustainably into Media workflows. The ambition is to move from fragmented experimentation to a repeatable AI delivery model that creates value across planning, activation, operations, reporting, optimisation, workflow automation and client-facing services.

• Partner with Media leadership and operational teams to identify where AI can improve effectiveness, efficiency, quality, speed or client impact across existing tools and new dev opportunities.
• Translate business pain points into clear solution hypotheses, AI use cases and requirements.
• Assess potential opportunities based on value, feasibility, risk, data availability, reusability and scalability.
• Establish BAU process across Media teams to identify, test and scale AI-enabled ways of working.
• Support business teams to articulate requirements clearly and understand the practical implications of AI-enabled change.

• Build, coach and develop a high-performing group of AI engineers, solution builders, analysts and technical contributors.
• Oversee the design, prototyping and development of AI solutions for Media workflows, including automation, agentic workflows, knowledge retrieval, planning support, reporting, insight generation and operational tooling.
• Establish common engineering standards, design principles, solution patterns and delivery practices for AI solutions across Media.
• Work with product, data engineering, platform, security and enterprise architecture teams to ensure solutions are integrated into the right systems and operating environments.
• Create a culture where AI engineering is focused on real business problems, measurable value and responsible adoption - not experimentation for its own sake.

• Ensure AI solutions are developed in line with dentsu policies, governance standards, data protection requirements and responsible AI principles.
• Identify risks relating to data, privacy, accuracy, bias, security, model performance, user adoption and operational dependency.
• Build appropriate testing, validation, monitoring, cost controls and human-in-the-loop controls into AI solutions.
• Establish feedback loops with users to improve solutions over time.

• Strong understanding of generative AI, machine learning concepts, automation, large language models, prompt engineering, retrieval-augmented generation and AI-enabled workflow design.
• Experience designing, building AI or automation solutions in a business environment leading technical or cross-functional teams.
• Ability to assess technical feasibility, data readiness, integration needs and model/tool suitability.
• Understanding of APIs, MCP, data pipelines, cloud platforms, software delivery practices and enterprise technology environments.
• Ability to guide prototyping and engineering activity from concept through to production-ready solutions.
• Strong appreciation of security, privacy, testing, quality assurance and responsible AI…