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Salary: USD 150,000 - 175,000 / annual
Fabric Health is a healthcare technology company focused on solving clinical capacity challenges through intelligent automation. The company unifies the care journey from intake to treatment, making care delivery 2-10x more efficient while empowering clinicians to focus on patient care. Trusted by leading healthcare organizations including Intermountain Health, OSF HealthCare, SSM Health, and MUSC Health, Fabric is backed by premier investors such as Thrive Capital, GV (Google Ventures), General Catalyst, and Salesforce Ventures.
As a Senior Software Engineer in Artificial Intelligence, you will lead the development of advanced language and voice technologies that transform patient-provider interactions. This is a hands-on, high-impact role at the intersection of innovation and production engineering, working cross-functionally to build intelligent dialogue systems and conversational AI infrastructure.
Key responsibilities include: designing and optimizing LLM applications (RAG, classification, summarization); prototyping and productionizing ML/AI features in Python; partnering with product and medical teams to develop safeguards for AI outputs; collaborating on APIs for LLM applications; creating automated evaluations for accuracy and performance; maintaining existing NLP and AI diagnosis components; developing analytics for system monitoring; deploying AI services end-to-end on AWS and Kubernetes; researching emerging AI tools and architectures; and contributing to healthcare AI strategy.
You should be passionate about deploying technology that empowers patients, excel at breaking down complex AI problems autonomously, stay current on machine learning and foundation models, and value robust testing and responsible AI practices. You thrive in cross-functional collaboration and communicate complex ideas clearly to technical and non-technical audiences.
Required qualifications: 5+ years software engineering or applied machine learning experience with focus on real-world AI/ML systems; proficiency in Python (Flask/FastAPI); 3+ years hands-on LLM and LLM agent experience; solid understanding of embeddings and embedding databases; NLP or speech processing experience; familiarity with modern frameworks (Hugging Face, OpenAI API, LangChain, LangGraph); cloud-native AWS and Kubernetes deployment experience; demonstrated ability to move models from research to production at scale; and effective cross-disciplinary communication skills.
Bonus qualifications include conversational agent experience, real-time voice communication (WebRTC, telephony), ASR/TTS, voice assistant work, multimodal AI interfaces, open-source model hosting/scaling/fine-tuning, and passion for improving healthcare access through applied AI.
