Remote GenAI Engineer

A well-respected, stable financial services organization based in Los Angeles, CA is seeking an AI Engineer to design and implement next-generation Generative AI solutions that power real-world business applications. This role focuses on building RAG (Retrieval-Augmented Generation) pipelines, vector databases, and multi-modal AI systems that transform unstructured data into scalable, intelligent tools. The ideal candidate will be a hands-on builder with experience developing AI pipelines and models in production environments - ideally coming out of Big Tech or top-tier AI teams - and comfortable leveraging modern AI frameworks and orchestration tools to deliver production-grade solutions. What You'll Do • Build and deploy RAG pipelines, AI agents, and multi-modal applications using frameworks such as LangChain, LangGraph, or similar orchestration tools. • Design and maintain vector databases and data ingestion pipelines to move unstructured data into embedding-based storage for retrieval and modeling. • Develop, fine-tune, and integrate LLMs and Generative AI models into production workflows and business systems. • Collaborate cross-functionally with engineers, data scientists, and product teams to design and deliver end-to-end AI solutions. • Optimize AI model performance, scalability, and cost in cloud environments (AWS, Azure, or GCP). • Document system designs, workflows, and technical processes to ensure scalability and reproducibility. • Stay current with emerging GenAI technologies, frameworks, and best practices. What We're Looking For • 5-7 years of experience in software or AI engineering, with at least 3+ years focused on machine learning, LLMs, or applied AI. • Strong programming skills in Python with experience using frameworks such as PyTorch, TensorFlow, or similar. • Hands-on experience working with tools such as HuggingFace, LangChain/LangGraph, n8n, or comparable orchestration frameworks (specific tools not mandatory). • Proven experience building RAG systems and integrating LLMs with external or enterprise data sources. • Background in Apply tot his job