Director, Generative AI Experience Engineering (EMEA) Ajouter aux favoris
- 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.
- 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.
- 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.
- 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.
- 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
- 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.
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