Hippocratic AI builds clinical-grade LLM agents for low-acuity healthcare tasks (post-discharge follow-up, chronic care check-ins, medication reconciliation). Series B in 2024 with strong clinical advisory board. The interview emphasizes regulated-industry AI engineering, clinical evaluation methodology, and the deep safety-engineering required for healthcare applications.
Process
Recruiter screen → 60-minute coding (Python preferred) → onsite virtual: 2 coding, 1 ML system design, 1 craft deep-dive, 1 behavioral with clinical safety lens. Cycle: 4–6 weeks.
What they actually ask
- Design a clinical-grade LLM agent with safety guardrails
- Design a real-time voice-agent pipeline (ASR → LLM → TTS) for patient calls
- Design an evaluation harness for clinical safety with physician review
- Coding: medium DSA, sometimes clinical-data-flavored
- Behavioral: ownership, regulated-industry care, mission alignment
Levels and comp (2026)
- SE: $185K–$250K total
- Senior SE: $260K–$355K total
- Staff / ML: $370K–$520K+ total
Prep priorities
- Be fluent in Python (most of the platform)
- Understand healthcare data (FHIR, HL7), HIPAA constraints, and clinical workflows
- Brush up on LLM safety / red-teaming, voice-agent architecture, and clinical evaluation
Frequently Asked Questions
Is Hippocratic remote-friendly?
Hubs in San Francisco and Austin. Many engineering roles remote within US.
How does Hippocratic compare to Abridge, Suki, or Nuance DAX?
Abridge focuses on clinical documentation. Suki is voice-driven scribe. Nuance DAX (Microsoft) is the incumbent. Hippocratic differentiates on patient-facing agents (not provider-facing). Comp competitive for vertical AI.
What is the engineering culture?
Mission-driven, careful, calmer than frontier-lab pace. Strong clinical-advisor culture; engineers expected to engage with safety and clinical context.