Director, Generative AI Experience Engineering (EMEA)

At AKQA (part of WPP), we believe in the imaginative application of art and science to create beautiful ideas, products and services. With an entrepreneurial and collaborative approach, we design adaptive digital products, services and experiences that capture the imagination and deliver meaningful returns for our clients.  At AKQA, you will help define the next era of AI-native customer experiences,  not as a future concept, but as live products and platforms already moving into the world.

The industry is entering a structural shift. Traditional digital experiences are becoming AI-native experiences, interfaces assembled in real-time around intent, conversation, retrieval and contextual generation. At AKQA, we are not exploring this future theoretically. We are already building it.

We are looking for a Director, Generative AI Experience Engineering to help define and deliver the next generation of AI-native customer experiences across commerce, content and customer interfaces for some of the world’s most ambitious brands.

This role sits at the intersection of AI systems engineering, generative experience design and modern frontend architecture leadership. We are not looking for a traditional engineering manager, nor a pure AI researcher removed from delivery. We are looking for a hands-on technical leader who can operate across architecture, engineering, experimentation, delivery and client advisory simultaneously.

You will lead and mentor a small engineering team whilst remaining close to the code, prototyping new ideas, shaping AI-native architectures and helping clients navigate AI transformation with confidence and clarity.

Based in a hybrid working environment, collaborating with global AKQA studios, you will work alongside some of the brightest minds in design, engineering and innovation, helping shape the future of AI-native experiences.

ROLE REQUIREMENTS

Technical Leadership

• Lead the design and architecture of AI-native experience platforms, from frontend rendering systems through to retrieval, orchestration and agentic workflows.
• Remain hands-on with engineering teams, contributing to prototypes, proof-of-concepts and production acceleration across emerging AI-enabled products and services.
• Manage and mentor a team of developers whilst driving engineering quality, technical direction and delivery standards.

AI Systems & Experience Engineering

• Build and shape AI-native customer experiences driven by intent, contextual generation, retrieval and adaptive orchestration.
• Work across modern LLM ecosystems including foundation models, retrieval pipelines, vector storage, embeddings, multi-agent systems and AI observability tooling.
• Design systems that support conversational rendering, dynamic content assembly, streaming UX and adaptive interfaces.
• Actively experiment with AI tooling, workflows and engineering methodologies, bringing forward-thinking ideas into production environments.

Client Advisory & Strategic Leadership

• Work directly with senior client stakeholders to shape AI transformation conversations, technical strategy and engineering roadmaps.
• Lead discovery sessions, workshops and architecture discussions, translating technical complexity into commercial and customer experience value.
• Act as the engineering authority within client engagements, confidently communicating what is technically viable, scalable and strategically valuable.

Innovation & Delivery

• Lead rapid proof-of-concepts, innovation initiatives and production acceleration across undefined and emerging technical territory.
• Operate comfortably in ambiguity whilst balancing experimentation, delivery quality and commercial realities.
• Drive AI-augmented engineering methodologies and continuously improve engineering processes, tooling and technical standards.

Technical skills and knowledge:

Strong experience across modern frontend engineering and AI-native architecture, with the ability to design and deliver scalable, production-ready systems.

• Frontend & Experience Engineering
  – Advanced React and Next.js architecture
  –  Server Components, streaming UX and edge rendering
  –  Component systems and frontend orchestration
• AI Ecosystems & Orchestration
  –  Experience across modern AI ecosystems including OpenAI, Gemini, Claude and OSS models
  –  RAG pipelines, vector databases, embeddings and chunking
  –  Tool calling, agentic systems, orchestration and memory frameworks
  –  Prompt engineering, prompt management and context engineering
  –  AI observability, evaluations, governance and guardrails
• AI-Augmented Engineering
  –  AI-assisted development tooling including Claude Code, Cursor and Codex
  –  Prompt-driven engineering and AI pair-programming workflows
• Cloud & Infrastructure
  –  Vercel & GCP preferred, with AWS and Azure also considered
  –  Serverless and edge infrastructure
  –  AI workload deployment and optimisation
  –  CI/CD pipelines and Infrastructure as Code
• Additional Technical Experience
  –  REST and GraphQL APIs
  –  Microservices and MACH architectures
  –  CMS, DXPs and MarTech ecosystems

QUALITIES AND CHARACTERISTICS

• Must come from a strong engineering or development background with deep frontend architecture capability.
• A naturally curious and experimental mindset with strong opinions around the future of AI-native experiences and modern engineering workflows.
• Comfortable operating as both a technical architect and client-facing advisor.
• Low ego, collaborative and delivery-focused, with the ability to inspire through technical credibility rather than hierarchy.
• A systems thinker who understands the relationship between retrieval, orchestration, rendering and customer experience outcomes.
• Proactive, resilient and comfortable operating within rapid experimentation cycles and evolving technical landscapes.
• Excellent communication skills with the ability to explain complex AI systems and engineering decisions to both technical and non-technical audiences.
• Passionate about emerging technologies, AI tooling and continuously evolving engineering methodologies.