Technical Commerce & AI Consultant | Agentic Commerce

Accenture • St. Louis, MO

1d

About The Position

Accenture Song’s Customer Technology – Commerce practice helps organizations design, build, and scale digital commerce ecosystems by integrating commerce platforms, customer data, marketing technology, and AI-powered decisioning. The practice applies Generative AI and Agentic AI to areas such as personalization, merchandising, pricing, campaign orchestration, and revenue growth.

The Agentic Commerce & AI Consultant designs and builds AI-powered commerce solutions using Generative AI and multi-agent orchestration frameworks. The role owns solution components and ensures deployments are scalable, secure, and aligned with business objectives within customer technology ecosystems. Work includes developing agentic systems and RAG architectures; engineering commerce data, knowledge, and orchestration pipelines; deploying services through cloud and containerized environments; and applying Responsible AI, evaluation, testing, and observability practices.

The consultant collaborates with clients and cross-functional teams, develops presentations and demonstrations, explains technical architectures in terms of business outcomes and ROI, contributes to reusable knowledge assets and accelerators, and mentors junior analysts. Travel may be required for client support up to 50%. Primary residency must be within 90 minutes of an approved Accenture office.

Requirements

• At least 4 years of experience building scalable AI or data-driven systems.
• Strong proficiency in Python and SQL, with hands-on experience deploying Generative AI and Agentic AI solutions.
• Experience with Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or LangGraph.
• Experience designing prompt flows, multi-agent orchestration pipelines, and schema-driven tool invocation such as MCP or similar standards.
• Experience integrating AI systems with enterprise APIs and backend commerce platforms.
• Hands-on experience with FastAPI, AWS, Azure, or GCP, and Databricks.
• Experience with vector databases and retrieval-augmented architectures.
• Understanding of Responsible AI principles and production monitoring standards.
• Working knowledge of cloud-native architectures, containerization, and CI/CD pipelines.
• Strong communication skills and ability to translate advanced AI concepts into business value.
• Structured problem-solving skills and ability to build scalable, client-ready solutions.
• Ability to travel for client support as required, up to 50%.
• Primary residency within 90 minutes of an approved Accenture office.

Nice To Haves

• Experience in digital commerce, MarTech, or customer technology ecosystems.
• Experience designing a semantic layer and knowledge graph.
• Experience with prompt engineering.

Responsibilities

• Design and implement Agentic AI systems for personalization, merchandising optimization, campaign orchestration, conversational commerce, and digital customer engagement.
• Develop multi-agent architectures coordinating planners, retrievers, reasoning agents, predictive models, and optimization components.
• Build and operationalize retrieval-augmented generation systems grounded in commerce knowledge, product taxonomies, business rules, and policy constraints.
• Define and manage data, knowledge, and context pipelines that support agent reasoning.
• Lead data preparation, integration, validation, and semantic modeling for commerce use cases.
• Architect orchestration pipelines integrating predictive models, LLM reasoning, decision APIs, enterprise tools, and backend services.
• Integrate scalable solutions within digital commerce platforms and composable commerce architectures.
• Use cloud platforms for scalable AI deployment and lifecycle management; develop modular services and deploy production-ready solutions in containerized, CI/CD-based environments.
• Use Databricks for large-scale modeling workflows and AI experimentation.
• Integrate vector databases, distributed knowledge systems, and in-memory state management for context-aware agent workflows.
• Apply Responsible AI practices, including structured tool access, context governance, logging and traceability, bias awareness, and drift detection.
• Implement LLM evaluation metrics, structured testing frameworks, and observability standards.
• Optimize multi-agent systems for scalability, reliability, and commercial impact.
• Collaborate with cross-functional teams and clients to align AI implementations with business objectives.
• Support development of client-ready presentations, demos, and value narratives.
• Translate complex AI architectures into clear business outcomes and ROI impact.
• Contribute to knowledge assets, reusable accelerators, and best practices.
• Mentor junior analysts and support team capability development.

Benefits

• Hands-on exposure to modern commerce platforms, composable architectures, CDPs, MarTech stacks, and AI orchestration frameworks.
• Collaboration with Song teams across Commerce, Experience, Marketing, and Data.
• Opportunity to contribute to reusable accelerators and AI-driven commerce solution assets.
• Opportunity to develop technical expertise and client-facing consulting skills through transformation programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed