Senior Full Stack AI Engineer (Natural Language Systems)
Builds and deploys production-grade real-time AI systems focused on speech processing, NLP, and LLM workflows for healthcare applications like transcription and clinical documentation. Requires 4+ years AI/ML experience with strong Python engineering skills.
160k – 220k/yr
Remote4+ YOEFullstack Engineering
About the role
Responsibilities
Drive Prompt's mission to improve healthcare through modern technology including AI
Lead AI projects from ideation → architecture → production → iteration until features are widely adopted and loved
Develop and deploy real-time AI systems involving speech and natural language understanding (e.g., transcription, summarization, classification)
Build robust model and prompt pipelines for LLM-powered workflows with high accuracy and monitoring standards
Partner with Product and Engineering to identify high-leverage AI opportunities and deliver measurable outcomes
Help develop Prompt's strategic AI roadmap across speech, NLP, and core automation workflows
Apply AI to improve client and internal operations including clinical documentation, customer support, and billing workflows
Develop a deep understanding of Prompt's product, customers, and the business of rehab therapy
Help grow and lead the AI team, including training and development of junior team members
Qualifications
4+ years of experience building AI/ML systems in industry or academia, with meaningful production ownership
Strong experience building and evaluating NLP and/or LLM systems (e.g., retrieval, summarization, classification, extraction, agent workflows)
Experience working with speech-related pipelines in production or near-real-time settings (e.g., speech-to-text, spoken intent classification, conversational AI)
Track record of benchmarking and iteratively improving accuracy, cost, and latency
Enthusiastic and pragmatic problem-solving mindset
Excellent communication skills, with the ability to explain complex AI concepts to non-technical stakeholders
Python (>3.9)
Docker (Basics)
AWS familiarity (S3, RDS, EC2) preferred
Willingness to learn and deeply understand the healthcare sector, specifically physical therapy, occupational therapy, and speech therapy
Nice-to-Haves
Experience building and optimizing real-time speech processing systems (latency, streaming, stability)
Experience with modern STT engines and their evaluation
Experience with modern TTS engines and voice pipeline integration
Experience designing, developing, and optimizing IVR applications
Experience working with CPaaS platforms (e.g., Twilio) for telephony workflows and conversational routing
Experience architecting ML/LLM evaluation pipelines and quality systems (offline + online evaluation, golden sets, regression testing)
Experience with recommendation systems, automation systems, or large-scale workflow orchestration
Familiarity with FastAPI, Pydantic, SQLAlchemy, PostgreSQL
Experience with CI/CD pipelines and production observability tooling
Experience building healthcare software and/or data processing pipelines
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