About the Client
Our client is a major retail chain with an extensive regional presence, currently launching an AI transformation initiative. They aim to leverage generative AI to revolutionize customer engagement and operational efficiency across their digital platforms and physical store network.
Key Responsibilities
- Develop and deploy Multi-Agent AI systems to automate complex retail workflows, such as personalized shopping assistants and automated supplier communications.
- Build and maintain RAG pipelines that allow LLMs to query real-time inventory levels, product catalogs, and loyalty program databases.
- Design and refine structured prompts and function-calling schemas to enable AI agents to perform actions like order tracking or processing returns.
- Implement automated evaluation frameworks to ensure AI-generated product descriptions and customer responses remain accurate and brand-compliant.
- Fine-tune open-source models for domain-specific retail tasks, including sentiment analysis of customer reviews and demand forecasting.
- Partner with the e-commerce team to integrate LLM capabilities into mobile apps and web platforms for enhanced product discovery.
Requirements
- Bachelor's degree in Computer Science, Data Science, or a related technical field.
- 3-5 years of experience in software engineering, with at least 1 year of dedicated experience building applications with Large Language Models.
- Strong proficiency in Python and hands-on experience with frameworks like LangChain, LangGraph, or LlamaIndex.
- Proven experience in developing Multi-Agent systems and managing vector databases (e.g., Pinecone, Milvus, or Qdrant).
- Solid understanding of API integration, particularly connecting LLMs to internal ERP or CRM systems.
- Familiarity with retail-specific data challenges, such as handling large-scale product metadata and customer behavior patterns.
