We are seeking a highly skilled and passionate Generative AI Developer to join our growing team. This role demands deep expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering, with a strong focus on driving business impact in the Retail and Consumer Packaged Goods (CPG) domain. The ideal candidate will be comfortable working at the intersection of technology and industry, building scalable and innovative AI solutions that support personalization, automation, and decision intelligence. The role also involves end-to-end project management, comprehensive documentation, proactive client and stakeholder communication, driving business development and account growth initiatives, along with strong technical expertise. Key Responsibilities Design, develop, and deploy GenAI solutions using LLMs such as GPT, Claude, LLaMA, or open-source equivalents. Build and optimize RAG pipelines leveraging vector databases (e.g., FAISS, Pinecone, Weaviate) and embedding models. Engineer, evaluate, and refine prompts to improve output accuracy and relevance across different use cases. Collaborate with data scientists, engineers, and retail/CPG domain experts to identify high-impact AI opportunities. Monitor, maintain, and fine-tune deployed models to ensure performance, scalability, and business alignment. Stay current on advancements in the GenAI and LLM ecosystem and assess applicability to ongoing and future initiatives. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline. 7+ years of hands-on experience with LLMs, NLP, and GenAI development. Strong understanding and implementation experience of RAG-based architectures. Proficient in Python, with working knowledge of frameworks and libraries like HuggingFace, LangChain, OpenAI APIs, and Transformers. Familiar with embedding techniques and vector databases (e.g., FAISS, Pinecone). Demonstrated ability to translate retail/CPG-specific business challenges into scalable AI solutions. Experience deploying AI solutions in cloud environments (AWS, Azure, or GCP). Preferred Qualifications Experience with multimodal LLMs or custom model fine-tuning. Integration of GenAI solutions into enterprise systems, BI tools, or customer-facing platforms. Knowledge of ethical AI, data governance, and responsible AI practices in production environments. #J-18808-Ljbffr