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Accenture

Advises businesses and runs their technology

Agentic AI & Commerce Architect

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeLondon, UK

About the Job

Requirements

  • At least 8 years of experience in AI/ML systems, including demonstrable experience designing and delivering generative AI and agentic AI systems in production.
  • At least 4 years of enterprise commerce delivery on Salesforce Commerce Cloud, Adobe Commerce, SAP Commerce, or composable/MACH stacks, or equivalent depth in adjacent enterprise platform delivery with a clear trajectory into commerce.
  • Proven experience designing LLM-based systems, including retrieval-augmented generation (RAG), tool-calling, multi-agent orchestration, and reasoning workflows.
  • Experience with vector retrieval architectures and embedding pipelines in production, including semantic search and RAG.
  • Experience designing AI governance frameworks covering auditability, human-in-the-loop (HITL), red teaming, and compliance controls.
  • Experience with AgentOps/LLMOps observability, tracing, and model evaluation in production.
  • Experience integrating commerce stacks with order management systems (OMS), product information management (PIM), digital asset management (DAM), customer relationship management (CRM), payments, and fulfilment systems.
  • Proficiency in Python, agent frameworks, vector databases, APIs/microservices, and distributed systems.
  • Experience with cloud delivery on AWS, Google Cloud Platform (GCP), or Azure, as well as CI/CD and cloud-native architecture.
  • Demonstrated leadership of complex, multi-region enterprise programs.

Responsibilities

  • Design and document multi-agent architecture blueprints, agentic orchestration patterns, knowledge and semantic layer blueprints, AI governance blueprints, and AgentOps/LLMOps architecture.
  • Design the knowledge architecture underpinning agent intelligence, including embeddings pipelines, vector retrieval, and semantic search structured around commerce-specific intent, product relationships, and category hierarchies.
  • Architect the integration layer connecting agentic systems to enterprise commerce stacks, including OMS, PIM, DAM, CRM, payments, pricing, and fulfilment, using API gateways, event buses, and agentic protocols such as MCP, A2A, ACP, and UCP.
  • Lead build-versus-buy decisions across LLM platforms, orchestration frameworks, vector stores, and agentic workbenches, and design multi-model routing strategies to avoid single-provider lock-in.
  • Embed AI governance, observability, and guardrail design as first-class architectural concerns, including audit logging, human-in-the-loop escalation, adversarial testing, and compliance controls.
  • Lead large-scale agentic commerce implementations across Salesforce Commerce Cloud, Adobe Commerce, SAP Commerce, and composable/MACH stacks, embedding agentic AI into live production environments.
  • Translate agentic commerce strategy into executable platform roadmaps grounded in clients' existing commerce stacks and data estates.
  • Lead architecture workshops with senior client stakeholders, presenting options with defined trade-offs, timelines, and business outcomes.
  • Develop total cost of ownership (TCO) models, effort estimates, and phased delivery roadmaps.
  • Provide architectural leadership across distributed, multidisciplinary delivery teams spanning AI, backend, data, cloud, and DevOps.
  • Guide the path from prototype to production by defining the architectural runway for rapid, CI/CD-enabled scaling of agentic solutions.
  • Define and oversee the AgentOps/LLMOps framework, establishing standards for production monitoring, tracing, model evaluation, and continuous improvement across delivery teams.
  • Define key performance indicators (KPIs) to measure agent performance, conversion uplift, operational efficiency, and return on investment (ROI).
  • Shape Accenture Song's agentic commerce architecture standards, reference architectures, and reusable accelerators.
  • Create industry-specific points of view (POVs), demos, and proposal assets for commerce pursuits.
  • Engage C-suite stakeholders and grow engineering talent within the practice.

Desired Qualifications

  • Experience with agentic commerce protocols, including MCP, A2A, ACP (OpenAI), and UCP (Google).
  • Experience with hyperscaler agentic platforms, including Google Vertex AI/Agent Dev Kit, Azure AI Foundry, and AWS Bedrock Agents.
  • Experience with GEO/AEO content architecture, including structuring product data for LLM discoverability.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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