5+ years of experience in backend software engineering, applied machine learning/search, or data-centric application development.GenAI & RAG Focus: 1–2 years of hands-on experience specifically optimizing AI and RAG architectures, prompt context strategies, and vector retrieval pipelines for LLM applications.Programming & Tooling: Advanced proficiency in Python and SQL, alongside familiarity with modern orchestration tools (e.g., Airflow, Prefect, Temporal).Unstructured Content Parsing: Deep experience using parsing frameworks (e.g., LlamaIndex, Unstructured.io, LangChain document loaders) to process complex layouts, tables, and unstructured documents.Vector & Search Engines: Hands-on experience working with vector databases, embeddings, and semantic search platforms (e.g., Pinecone, pgvector, Weaviate, Qdrant, Azure AI Search).Evaluation Frameworks: Familiarity with RAG and LLM context evaluation frameworks (e.g., Ragas, TruLens, Arize Phoenix) to measure retrieval recall, precision, and groundedness.Data Security & Privacy: Practical experience handling sensitive healthcare data (PHI/PII) within high-compliance software environments.
Deadline:01 Dec 2026