We are seeking a versatile and passionate AI to join our data science and engineering team. You will be instrumental in bridging the gap between data science research and production-ready applications, building scalable machine learning systems that drive business value. This role requires a strong balance of software engineering principles and ML expertise. Key Responsibilities Design, develop, and deploy end-to-end AI pipelines, focusing on integrating Large Language Models (LLMs) and Foundation Models into production environments. Work closely with stakeholders to transition AI prototypes and experimental agents into scalable, production-grade systems, implementing modern LLM Ops practices. Develop robust, efficient code using Python and frameworks such as LangChain, LlamaIndex, or AutoGPT, alongside traditional libraries like PyTorch or TensorFlow when needed. Implement advanced monitoring for AI applications, focusing on output quality, hallucination detection, and performance tracking (e.g., using RAGas or Arize Phoenix). Collaborate with Data Engineers to build efficient data pipelines for vector databases (Chroma, Pinecone, Weaviate) and optimize context retrieval for RAG. Stay at the forefront of the rapidly evolving Generative AI landscape, exploring new techniques in prompt engineering, fine-tuning, and agentic workflows.