Job details
About this role
Role overview
Lead the design and delivery of next-generation AI-native customer experiences across commerce, content, and customer interfaces. This senior, hands-on technical leadership role sits at the intersection of AI systems engineering, generative experience design, and modern frontend architecture, partnering with client stakeholders to translate emerging AI capabilities into production-ready platforms.
Responsibilities
- Architect AI-native experience platforms spanning frontend rendering systems, retrieval pipelines, orchestration, and agentic workflows. - Remain hands-on with engineering teams by contributing to prototypes, proof-of-concepts, and production acceleration across AI-enabled products. - Manage and mentor a small team of developers, driving engineering quality, technical direction, and delivery standards. - Build customer experiences driven by intent, contextual generation, retrieval, and adaptive orchestration, including conversational rendering, dynamic content assembly, streaming UX, and adaptive interfaces. - Advise senior client stakeholders on AI transformation, technical strategy, and engineering roadmaps, leading discovery sessions, workshops, and architecture discussions. - Lead rapid proof-of-concepts and innovation initiatives, balancing experimentation, delivery quality, and commercial realities in ambiguous, evolving technical territory.
Requirements
- Strong engineering or development background with deep frontend architecture capability and experience delivering scalable, production-ready systems. - Advanced React and Next.js architecture, including Server Components, streaming UX, edge rendering, and component systems. - Experience across modern AI ecosystems (e.g., OpenAI, Gemini, Claude), retrieval pipelines, vector storage, embeddings, multi-agent systems, and AI observability tooling. - Familiarity with AI-assisted development tooling and prompt-driven engineering workflows. - Cloud and infrastructure experience with serverless and edge deployment, CI/CD pipelines, and Infrastructure as Code; Vercel and GCP preferred. - Working knowledge of REST and GraphQL APIs, microservices, MACH architectures, and CMS/DXP/MarTech ecosystems, plus strong communication skills for technical and non-technical audiences.
Nice to have
- Background in evaluations, governance, and guardrails for AI systems. - Comfort operating as both a technical architect and a client-facing advisor, with a low-ego, collaborative, delivery-focused style.
Benefits and work setup
- Hybrid working model with required in-office days, collaborating with global studios. - Reasonable adjustments and flexibility discussed with the hiring team during the interview process. - Equal opportunity employer committed to a respectful, inclusive culture.