Join our dynamic team as a Generative AI Engineer, focusing on integrating cutting-edge AI technologies into user-centric applications. This role is pivotal in developing intelligent systems powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) pipelines, ensuring seamless and intuitive frontend experiences. You will be instrumental in bringing advanced AI capabilities to life.

Spearhead the design and implementation of advanced Generative AI solutions using leading LLMs like GPT, Claude, and LLaMA. Optimize Retrieval-Augmented Generation (RAG) pipelines with vector databases, including ChromaDB for local use and Databricks Mosaic ML Vector Stores. Develop sophisticated agentic workflows and conversational AI agents using frameworks such as LangGraph and OpenAI. Enhance accuracy through vectorization with models like GTE-large and BGE, with opportunities for fine-tuning. Collaborate cross-functionally to embed Gen AI features into our product suite.

A strong foundation in LLMs, prompt engineering, and transformer architectures is essential. Practical experience with RAG architectures, vector search, and embedding models is required. Proficiency in Python and relevant libraries like LangChain, Transformers, OpenAI SDK, or Hugging Face is necessary. Familiarity with agentic frameworks such as AutoGen, OpenAI, CrewAI, or LangGraph is expected. Experience deploying AI models via APIs or microservices is a key requirement. A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related discipline is preferred, alongside experience with cloud platforms (AWS, GCP, Azure) and CI/CD pipelines.