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UpDoc is building the first clinically validated, physician-supervised AI agent for chronic disease management. Founded by Stanford physicians, the company is seeking a Clinician Scientist (MD) to define and evaluate the clinical intelligence powering UpDoc's AI-enabled products.
In this role, you will work at the intersection of clinical reasoning, AI evaluation, and clinical data integration. You'll define clinical reasoning frameworks, expected system behavior, and safety boundaries for chronic disease products, including decision logic, uncertainty handling, risk assessment, escalation protocols, and safeguards. You'll design and execute rigorous clinical evaluations using scenarios, datasets, rubrics, and acceptance thresholds, using failures and edge cases to drive product improvements.
You'll contribute to clinical validation studies, outcomes analysis, and research supporting new capabilities. Working closely with clinical data and EHR systems, you'll help determine what information UpDoc needs, how EHR data should be interpreted, and how product workflows map to real-world clinical practice. You'll serve as a clinical and technical bridge internally and externally, partnering with Product, Engineering, health-system informatics teams, and clinical stakeholders on integrations, implementation, and workflow optimization.
This is a remote position ideal for a physician who thinks systematically about clinical decision-making and can translate nuanced reasoning into testable, explicit expectations. You should be comfortable working with data, APIs, EHR concepts, and AI systems, even without formal engineering training.
REQUIREMENTS:
- MD or DO degree with completed residency training, board certification or eligibility, and meaningful direct patient-care experience
- Strong clinical judgment with ability to reason rigorously about ambiguous cases, uncertainty, edge cases, and risk; ability to translate reasoning into explicit, testable expectations
- Strong analytical skills and technical fluency; comfort with data, APIs, EHR concepts, and AI systems
- Ability to work effectively with Engineering, AI/ML, Data, Product, clinical teams, and external health-system stakeholders
HIGHLY DESIRED:
- Experience developing or evaluating AI-enabled clinical products (clinical evaluation datasets, rubrics, model evaluation, AI safety and quality)
- Experience in clinical research, clinical validation, or FDA-regulated software environments
- Experience in chronic disease management, primary care, cardiometabolic health, or longitudinal care
- Clinical informatics experience or training; familiarity with EHRs, FHIR, healthcare interoperability, or health-system integrations
- Comfort with technical tools such as Python, SQL, notebooks, data analysis, or AI evaluation tooling
