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# Technical Commerce & AI Consultant | Agentic Commerce

- **Company:** Accenture
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $70,350.0 - $196,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Continuous Integration, Data Cleansing, Graph Database, Python (Programming Language), Knowledge-Based Systems, Performance Tuning, Redis, Salesforce.Com, SQL Databases, SAP Customer Experience, Data Logging, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Backend, Fastapi, Build Management, Adobe, Containerization, Data Analytics, Virtual Agents, Databricks
- **Published:** September 27, 2026
- **Apply:** https://www.careerjet.com/job/us2816c475002cf91ae8476c37ce98848f/eaa

## About the Role

* 4+ years of experience building scalable AI or data-driven systems, preferably within digital commerce, MarTech, or customer technology ecosystems. Experience should include:

 * Strong proficiency in Python and SQL, with hands-on experience deploying Generative AI and Agentic AI solutions.
 * Experience working with Agentic AI frameworks (LangChain, LlamaIndex, CrewAI, AutoGen, LangGraph).
 * Experience designing prompt flows, multi-agent orchestration pipelines, and schema-driven tool invocation (e.g., MCP or similar standards).
 * Experience integrating AI systems with enterprise APIs and backend commerce platforms.
 * Hands-on experience with FastAPI, AWS/Azure/GCP, and Databricks.
 * Experience working 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 with the ability to translate advanced AI concepts into business value.
 * Structured problem-solving skills and ability to build scalable, client-ready solutions.
 * Experience with designing of a semantic layer and knowledge graph
 * Experience with prompt engineering

## Description

As an Agentic Commerce & AI Consultant, you will design and build AI-powered commerce solutions using Generative AI and multi-agent orchestration frameworks. You will take ownership of solution components, ensuring scalable, secure, and business-aligned deployments within customer technology ecosystems.
Agentic Commerce Solution Development
Design and implement Agentic AI systems enabling intelligent decision workflows across:
Personalization engines
Merchandising optimization
Campaign orchestration
Conversational commerce
Digital customer engagement platforms
Develop multi-agent architectures coordinating planners, retrievers, reasoning agents, predictive models, and optimization components.
Build and operationalize retrieval-augmented generation (RAG) systems grounded in structured commerce knowledge, product taxonomies, business rules, and policy constraints.
Data & Orchestration Engineering
Define and manage data, knowledge, and context pipelines to support effective 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
Ensure scalable integration within digital commerce platforms (e.g., Adobe Commerce, Salesforce Commerce, SAP CX, composable commerce architectures).
Cloud & Deployment
Leverage AWS, Azure, or GCP for scalable AI deployment and lifecycle management.
Develop modular services using FastAPI and deploy production-ready solutions using containerized and CI/CD-based environments.
Utilize Databricks for large-scale modeling workflows and AI experimentation.
Integrate vector databases, distributed knowledge systems, and in-memory state management (e.g., Redis) for context-aware agent workflows.
Responsible AI & Performance Optimization
Apply Responsible AI principles including:
Structured tool access
Context governance
Logging and traceability
Bias awareness
Drift detection
Implement LLM evaluation metrics, structured testing frameworks, and observability standards.
Continuously optimize multi-agent systems for scalability, reliability, and commercial impact.
Consulting & Client Engagement
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.


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