Agentic AI Commerce Search Architect

Job description

Role: AI Commerce Search Sr. Engineer/Architect Location: London Level: Associate Manager About Accenture SongAccenture Song accelerates growth and value for our clients through sustained customer relevance. Our capabilities span ideation to execution: growth, product and experience design; technology and experience platforms; creative, media and marketing strategy; and campaign, content and channel orchestration. Within Song, our Commerce & AI practice helps organizations design, build, and scale modern digital commerce ecosystems - embedding Generative AI and Agentic AI into commerce to enable real-time personalization, autonomous merchandising, intelligent discovery, and customer engagement at scale. Visit us at: www.accenture.com/song About the roleAI is rewriting how people find and buy. Discovery is shifting from keyword search boxes to conversational, agent-mediated experiences - across both a brand's owned platforms and the AI surfaces where customers increasingly begin their journey. We are looking for a technically strong architect to lead the design and delivery of Google-powered AI commerce experiences - with intelligent, AI-native search and discovery at the core, extending across the wider set of on-platform agentic commerce use cases. You will work at the intersection of enterprise commerce platforms and Google's agentic AI stack - Vertex AI Search for Commerce, Gemini Enterprise (GECX), Google Cloud Agents, Vertex AI Agent Builder / ADK, and the Customer Engagement Suite - translating commerce strategy into production-grade, grounded, and commercially reliable AI systems. This role leans into Google Cloud AI platforms as the delivery foundation. Search and discovery is your anchor specialism, but your remit spans the broader on-platform agentic commerce agenda: conversational commerce, personalization, merchandising optimization, product knowledge and content, and the GEO / AI-native discoverability that determines whether a brand shows up accurately in LLM-mediated discovery. You are hands-on, technically rigorous, and 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. Key ResponsibilitiesOwning the technical design of AI-powered commerce search and discovery workstreams on Vertex AI Search for Commerce — relevance tuning, ranking, retrieval, merchandising controls, and query understanding — and ensuring the approach is scalable, grounded, and aligned to client constraints. Designing broader on-platform agentic commerce experiences on Google's stack — conversational commerce, guided shopping, personalization and next-best-action, and merchandising optimization — using Gemini Enterprise (GECX), Google Cloud Agents, and Vertex AI Agent Builder / ADK. Designing the knowledge and data architecture that underpins search and agent intelligence — structured product data, embedding pipelines, vector retrieval, semantic search, and RAG grounded on commerce-specific intent, product relationships, and category hierarchies. Architecting integration between Google AI surfaces and the enterprise commerce stack - OMS, PIM, DAM, CRM, payments, and fulfilment — via APIs, event-driven patterns, and emerging agentic protocols (MCP, A2A, ACP). Leading GEO / AEO and AI-native discoverability design — structuring and exposing product content so brands remain visible, accurate, and preferred across AI-driven discovery surfaces. Contributing to build-vs-buy decisions across Google AI platform services, LLM/model choices (incl. Model Garden), orchestration frameworks, and vector stores — with a well-reasoned technical point of view grounded in delivery experience. Embedding AI governance, observability, and responsible AI into design as first-class concerns - audit logging, human-in-the-loop escalation, grounding/hallucination controls, brand safety, and performance monitoring. Providing technical leadership to delivery teams — guiding engineers, reviewing technical decisions, and maintaining architectural coherence across the workstream lifecycle. Leading technical workshops and architecture reviews with client stakeholders — presenting options with clear trade-offs, effort implications, and business outcomes for both technical and non-technical audiences. Supporting the development of Accenture Song's AI commerce capability — contributing to reference architectures, accelerators, and points of view that advance our delivery standards. What We Are Looking For Required Experience ~6 years of professional experience in technical architecture, solution engineering, or software engineering — with meaningful delivery across enterprise platforms and a growing specialism in AI and agentic systems. Hands-on experience designing and delivering AI-powered search, discovery, or recommendation systems in production - relevance, ranking, retrieval, and query understanding. Demonstrable, hands-on experience with Google Cloud AI platforms applied to commerce - one or more of Vertex AI Search for Commerce, Gemini Enterprise (GECX), Vertex AI Agent Builder / ADK, or the Customer Engagement Suite. Hands-on experience with Generative AI and agentic systems - LLM-powered application design, retrieval-augmented generation (RAG), and at least one agent framework (e.g. LangGraph, LangChain, LlamaIndex, CrewAI). Experience designing and building data and context pipelines for AI systems -=embedding pipelines, vector databases, and semantic search over structured commerce data. Hands-on delivery on at least one major enterprise commerce platform - such as Salesforce Commerce Cloud, Adobe Commerce, Commercetools, SAP Commerce, or a composable / MACH-aligned stack - and a solid understanding of how these integrate with surrounding enterprise systems. Familiarity with emerging agentic commerce protocols - MCP, A2A, or ACP - and how they connect AI agents to commerce systems and product data. Working knowledge of cloud-native services and CI/CD-based delivery (GCP preferred). Understanding of AI governance and responsible AI - observability, tracing, auditability, grounding, and guardrails in production AI systems. Experience leading technical design sessions and presenting architecture options to senior client or stakeholder audiences. Preferred Experience Familiarity with GEO (Generative Engine Optimization) and AI-native search — how product data must be structured and exposed to remain visible and accurate in LLM-mediated discovery. Experience with Google's broader agent ecosystem - Model Garden, Agent Engine, AgentOps, and grounding/RAG on enterprise data. Hands-on AgentOps / LLMOps practices - production monitoring, model evaluation, tracing, and continuous improvement for deployed AI systems. Exposure to composable commerce patterns - MACH principles, headless commerce, and API-first design - and how they enable flexible AI integration. Experience contributing to technical proposals, reference architectures, or delivery accelerators in a consulting or professional services context. What’s in it for you: Our Total Rewards consist of a competitive basic salary, annual performance bonus, opportunities to acquire equity and a wide range of health and wellbeing benefits. These include perks such as: Up to 30 days of leave to spend each year plus 3 extra volunteering days per year for charitable work of choice. Family-friendly and flexible work policies. Attractive pension plan with financial wellbeing support and resources. Private healthcare insurance plan and Mental Wellbeing support. Employee Assistance Programme, Career Development and Counselling. A range of generous Parental Leave offerings. Flexibility and mobility are required to deliver this role as there will be requirements to spend time onsite with our clients and partners to enable delivery of the outstanding services we are know