Role overview
- Multi-agent consensus : specialized models debate cases before reaching conclusions.
- RAG at scale : pipelines ingesting thousands of clinical guidelines curated for LLMs.
- Real-time inference : optimize latency and throughput for millions of daily consultations.
- Domain workflows : custom reasoning chains for condition- and specialty-specific care.
- HIPAA-compliant NLP : extract structured data from patient conversations.
- EHR connectivity : integrate with QHINs for automated retrieval/reconciliation.
- Intelligent triage : route cases between AI and clinicians via complexity scoring.
- Documentation : generate notes that conform to provider protocols and coding rules.
- Emergency detection with sub-second human escalation.
- Validation layers targeting 99%+ plan accuracy vs. clinical standards.
- Distributed systems for explosive peak loads and rapid user growth.
- Fail-safes for regulated, critical-path decisions.
Basic qualifications
- BS in CS (or equivalent experience). Hard-science degrees (Physics/Math/Engineering) welcome.
- Startup DNA preferred: founding engineer, founder, or deep early-stage experience.
- Proven self-direction with excellent cross-functional collaboration.
- 7+ years engineering; expert in LLMs and generative AI .
- Deep experience with OpenAI GPT , Anthropic Claude , LLaMA , and other FMs.
- Strong prompt engineering , fine-tuning , and model optimization in specialized domains.
- Built real-time production AI systems.
- Proficient in Python and TensorFlow/PyTorch ; modern AI tooling.
Preferred qualifications
- Healthcare/med-tech AI experience; familiarity with HL7 , FHIR , clinical workflows.
- Safety, bias detection, and fairness in medical AI.
- Domain NLP research/implementation.
- Worked with clinicians or in regulated environments.
- Publications in AI/ML (healthcare/safety-critical a plus).
- Seed/Series A startup experience.
- Advanced degree in CS/AI/ML or related field.
Benefits
- Competitive base + meaningful equity at a seed-stage company with top-tier investors.
- Direct impact building AI that transforms care for millions of patients.
- High autonomy and technical leadership , reporting to the CEO.
- Access to cutting-edge models, tooling, and clinical advisors.
- Collaboration with leading physicians and AI researchers.
- Benefits reimbursement.
Tags & focus areas
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