Join our innovative team as a Generative AI Engineer, playing a crucial role in integrating advanced AI/ML/GenAI technologies into our services. You will focus on creating intelligent, agentic applications powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) pipelines. Your work will ensure seamless user experiences through intuitive and responsive frontend interfaces.

This role is central to our mission of delivering cutting-edge Engineering as a Service, requiring a blend of deep technical expertise and a user-centric approach to AI development.

Design and implement sophisticated Generative AI solutions leveraging LLMs such as GPT, Claude, and LLaMA. Develop and optimize RAG pipelines using various vector databases, including ChromaDB for local development and Databricks Mosaic ML Vector Stores. Build and maintain dynamic agentic workflows and conversational AI agents using established frameworks like LangGraph and OpenAI.

Execute vectorization using models like GTE-large and BGE, with the flexibility to fine-tune them for enhanced accuracy. Collaborate effectively with backend and application development teams to seamlessly integrate GenAI capabilities into our product ecosystem.

A strong grasp of LLMs, prompt engineering techniques, and transformer architectures is essential. Candidates must possess hands-on experience with RAG architectures, vector search mechanisms, and embedding models. Proficiency in Python is a must, along with experience in libraries such as LangChain, Transformers, OpenAI SDK, or Hugging Face. Familiarity with agentic frameworks like AutoGen, OpenAI, CrewAI, or LangGraph is required.

Experience in deploying AI models through APIs or microservices is also a key requirement for this role. A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field, along with cloud platform experience (AWS, GCP, Azure) and CI/CD pipelines, is preferred.