Engineer 

Job Description

Responsibilities

• Challenge unclear or technically weak requirements with practical alternatives.
• Translate clinical and product requirements into clear, testable technical specifications.
• Proactively identify risks and failure modes before implementation.

GenAI & Conversational AI (80%)

• Design and build end-to-end RAG pipelines (ingestion, chunking, embeddings, vector stores, retrieval, generation).
• Integrate and evaluate LLMs (OpenAI, Claude, Gemini) with a focus on response quality, hallucination mitigation, and healthcare safety.
• Develop AI services using LangChain/LangGraph, Python, Flask, and REST APIs.
• Build prompt engineering and LLM evaluation frameworks covering relevance, accuracy, safety, and tone.
• Implement and optimize vector databases (FAISS, Pinecone, Weaviate) and embedding pipelines.

Machine Learning & Signal Engineering (1020%)

• Develop ML models and health signals from physiological data (CGM, HRV, sleep, activity, heart rate).
• Engineer meaningful features for time-series health data and evaluate model confidence, accuracy, and edge cases.
• Apply explainable and clinically defensible ML approaches, choosing the simplest effective model.

Data Engineering

• Build, debug, and maintain data pipelines in Python and C#.
• Manage end-to-end health data flow from connected devices through ingestion, transformation, storage, and AI consumption.
• Resolve data quality issues and work with structured/time-series data, including normalization, windowing, gap handling, sensor dropouts, and timezone-aware aggregation.

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