Senior Software Engineer, AI
AI Summary
Leads development of a patient-facing conversational AI agent, implementing scalable voice and multimodal systems, prompt engineering, and LLM infrastructure for a physician-supervised chronic disease management platform.
About this role
About UpDoc
At UpDoc, we are building the first clinically validated, physician-supervised AI agent that manages chronic diseases. We are an early-stage startup founded by Stanford physicians.
We are seeking a talented and motivated senior engineer to join our team. You will primarily work on UpDoc’s patient-facing conversational agent. This is a fully remote position.
Who You Are
You’re an experienced senior engineer with a backend tilt. You’re well-versed in all things web and have experience building LLM applications end-to-end, even if not in a professional context. You follow the AI/LLM space closely, play with new technologies as they come out, and are excited to use these technologies to build safe, reliable medical AI systems.
What You'll Do
Lead the development of our patient-facing conversational agent
Implement a scalable, low-latency system for voice/multimodal conversations
Implement rigorous prompt engineering processes and develop useful metrics for system evaluation
Identify where fine-tuning and alignment might be valuable, and create data pipelines to enable fast experimentation
Work with other backend engineers to deploy AI models and chat/voice APIs
Help identify, evaluate, and implement emerging LLM technologies, tools and frameworks
Collaborate with clinical experts to validate performance and medical accuracy
Work on developing backend services using FastAPI and Pydantic
What You’ll Need
5+ years of professional software development experience, including 2+ years of experience with backend web development
Experienced and comfortable working with type-hinted, modern Python
2+ years of experience building end-to-end LLM applications, personally or professionally
Experience integrating/optimizing LLMs in production environments
Knowledge of evaluation frameworks
Knowledge and experience with MLOps/LLMOps best practices
Experience building AI infrastructure from 0 -> 1
Experience with cloud platforms (especially Azure) and containerization technologies
Highly Desired
Professional experience building end-to-end LLM-powered applications
Experience with model fine-tuning/alignment
Experience in an early stage startup environment
Experience with healthcare industry standards, such as FHIR, and regulations, including HIPAA and SOC 2
Skills
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