Senior/ AI Engineer

Main Responsibilities

• Assistant Development: Design and implement the core logic for a multi-agent system that assists pharmacists with drug information, dosage calculations, and clinical decision support.
• Advanced RAG Pipelines: Build and optimize high-accuracy Retrieval-Augmented Generation systems using vector databases to ensure the AI provides evidence-based medical answers.
• Agentic Workflows: Develop agents capable of reasoning through complex tasks, such as cross-referencing a customer's medication history from the CDP with new prescriptions to flag potential risks.
• Model Optimization: Lead the fine-tuning of LLMs (e.g., Llama 3, GPT-4, or specialized medical models) for Vietnamese medical terminology and Pharmacity's specific business context.
• Evaluation & Safety: Create rigorous evaluation frameworks (LLM-as-a-judge) to measure hallucination rates, medical accuracy, and safety, ensuring the AI never provides harmful advice.
• Prompt Engineering: Design, test, and version-control sophisticated system prompts and few-shot examples to steer model behavior.
• Production Deployment: Work with DevOps and Engineering teams to deploy models as scalable microservices, ensuring low-latency responses for real-time in-store use.

Requirements

• Bachelor's, Master's, or Ph.D. in Computer Science, AI, Mathematics, or a related field.
• 3-5 years of experience specifically building LLM-based systems, including RAG and Agentic frameworks (e.g., LangChain, LlamaIndex, AutoGen, or CrewAI).
• Deep understanding of transformer architectures, tokenization, embeddings, and semantic search.
• Mastery of Python and deep learning frameworks (PyTorch or TensorFlow).
• Experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate, or pgvector).
• Cloud & MLOps: Proven ability to deploy models on cloud platforms (AWS, Azure, or GCP) using containerization (Docker, Kubernetes).
• Experience with frameworks like RAGAS or TruLens for evaluating LLM outputs.
• A portfolio of production-grade AI projects (GitHub or technical case studies).
• Experience in Healthcare, E-commerce, omni-channel is a major plus due to the high requirement for accuracy.