Join our dynamic team as an innovative Generative AI Engineer, specializing in AI/ML/GenAI integration within an Engineering as a Service framework. You will play a pivotal role in connecting advanced Generative AI technologies with exceptional user experiences.

This position involves spearheading the development of intelligent, agentic applications powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) pipelines. Your contributions will directly impact the delivery of intuitive and responsive frontend interfaces, pushing the boundaries of AI-driven solutions.

Key responsibilities include designing and implementing robust Generative AI solutions leveraging LLMs such as GPT, Claude, and LLaMA. You will develop and optimize RAG pipelines utilizing vector databases, including ChromaDB for local development and Databricks Mosaic ML Vector Stores.

Furthermore, you will construct and manage agentic workflows and conversational AI agents using established frameworks like LangGraph and OpenAI. The role also involves performing vectorization with models like GTE-large and BGE, with opportunities for fine-tuning to enhance accuracy. Close collaboration with backend and app teams is essential for seamless integration of Gen AI capabilities into our products.

We require a deep understanding of LLMs, prompt engineering, and transformer architectures, coupled with hands-on experience in RAG architectures, vector search, and embedding models. Proficiency in Python is essential, along with familiarity with libraries such as LangChain, Transformers, OpenAI SDK, or Hugging Face.

Experience with agentic frameworks like AutoGen, OpenAI, CrewAI, or LangGraph is necessary. You should also have experience deploying AI models via APIs or microservices. Preferred qualifications include a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field, along with experience in cloud platforms (AWS, GCP, Azure) and CI/CD pipelines.