SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Heidi Health is an AI-powered care partner that supports clinicians with documentation and care delivery. The company has returned 18+ million hours to clinicians and supported 73+ million patient visits across 116 countries, with 2 million patient visits weekly powered by Heidi. Backed by nearly $100M in funding, Heidi partners with major health systems including the NHS, Beth Israel Lahey Health, and Monash Health.
The New Bets squad builds Heidi's next-generation products. You'll work on zero-to-one engineering with immediate distribution advantage—your prototypes launch directly to clinicians already using Heidi daily, providing rapid feedback within a week. This is full-stack ownership: React/TypeScript frontends, Python services, LLM pipelines, prompts, retrieval systems, and evaluation harnesses. You'll also build onboarding flows, data migrations, and internal dashboards as needed.
You'll ship weekly, demo your work, and let real usage inform decisions. Some bets will be killed; most don't survive contact with real clinics. Successful products graduate into staffed product lines that inherit your code. This requires fast prototyping code and production-ready code for winners.
Responsibilities include: building new products end-to-end (React, Python, LLM/voice pipelines); turning one-page theses into working v0s in days; making AI features trustworthy and compliant for clinical use; shipping weekly with demos; spending time with clinicians to understand workflows and blockers; collaborating with commercial teams on business cases; instrumenting everything for usage, latency, and failure analysis; and handing off winners to staffed teams or continuing development.
Required: 3+ years shipping production software; full-stack fluency (Python backend, React/TypeScript frontend); working knowledge of LLM systems (prompting, retrieval, embeddings, evaluation); experience building with AI tools (Cursor, Claude Code); cloud fluency (AWS or GCP); testing-in-production mindset with observability; product instincts; speed as a habit; and strong opinions weakly held. Healthcare experience not required but genuine passion for improving healthcare is important.
