Agentic Commerce Architect

Role- Agentic Commerce Architect

Location- London

Level- Manager

Accenture Song accelerates growth and value for our clients by combining creativity, technology, and data-driven intelligence. Within Song, our Commerce & AI practice helps organisations design, build, and scale modern digital commerce ecosystems - embedding Generative AI and Agentic AI into commerce to enable real-time personalisation, autonomous merchandising, and intelligent customer engagement at scale.

About the role...

We are entering an exciting era of agentic commerce where AI agents, conversational interfaces, and intelligent systems are reshaping how people discover, evaluate, and buy online. We are looking for technically strong architects who can help design and deliver the systems that make this real - working at the intersection of enterprise commerce platforms and emerging agentic AI technologies.

You are an experienced technical architect with hands-on delivery experience across enterprise commerce platforms and a growing, demonstrable specialism in Generative AI and agentic systems. You are comfortable owning the technical design of a solution workstream, making well-reasoned build vs. buy decisions, and translating complex architecture into clear recommendations for both engineering teams and senior client stakeholders.

You do not need to have designed enterprise-scale agentic systems end-to-end, but you must have meaningful hands-on experience with the core components: LLM-powered applications, RAG architectures, agent frameworks, and enterprise platform integration. You are intellectually curious, technically rigorous, and energised by working at the frontier of what is currently possible in commerce AI.

Key Responsibilities

Owning the technical architecture of agentic commerce solution workstreams within enterprise delivery programmes, designing system components, integration patterns, and ensuring the overall technical approach is sound, scalable, and aligned to client constraints.

Designing and documenting agentic AI solution architectures - including multi-agent patterns, LLM-powered applications, retrieval-augmented generation (RAG) systems, and orchestration pipelines

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