À propos
HealthLeap builds AI that helps clinicians prioritize patients, surfaces the right data, and gets patients the care they need earlier, so they can leave the hospital sooner. HealthLeap integrates with hospital electronic health record systems, screens 100% of patients daily, and risk-ranks them in real time. Clinicians at Cedars-Sinai and Penn Medicine start every morning with HealthLeap with Houston Methodist, Emory, and Intermountain Health deploying now. Real results: 39% more diagnoses. 4 days earlier detection. $11M/year ROI for our first site at Cedars Sinai. 7 revenue growth in 7 months. We started with malnutrition. We're expanding to every major condition to ensure no patient falls through the cracks. Sequoia and First Round are backing us to build the platform that screens every patient for everything and drives tangible outcomes. We're ~15 people. >$7M raised. SF-based, hybrid-friendly. Early enough to shape the product. Late enough to know it works. Results that are changing lives. Why You
You've built systems that handle real scale - not toy projects, real data, real users, real uptime requirements. You've debugged distributed systems at 2am. You've dealt with messy third-party APIs that had no documentation. You're the person who figures things out when the docs don't help. What You'll Do
Build data pipelines that process millions of patient records daily Parse 50,000+ clinical notes per patient using LLMs - without hallucinating Own infrastructure on AWS and Kubernetes - deploy it, monitor it, fix it when it breaks Design systems for high concurrency and reliability - clinicians depend on this every morning Build feature engineering pipelines for ML models What We're Looking For
5+ years backend engineering experience Deep experience with distributed systems and highly concurrent workloads Solid with databases, data pipelines, ETL processing Comfortable with AWS, Kubernetes, and infrastructure-as-code You figure things out - even when documentation doesn't exist Nice To Have
Experience with healthcare data standards (FHIR, HL7v2) Background in LLM infrastructure or applied AI systems This Role Is Not For You If
Startup unpredictability feels like chaos to you. We find it exciting. You need detailed specs before you start. We figure it out as we go. You've never owned something end-to-end. Here, you own outcomes, not tasks. You wait to be told what to do next. We need people who see what's needed and do it. You're looking for a 9-5 with predictable hours. We care about deep work and deep rest (we have a minimum leave policy), but when a hospital go-live is on the line, we show up - even if that means a 60+ hour week. You see collaboration as interruption. We see it as leverage. The best engineers here are constantly pulling each other in - quick Slacks, 5-minute calls, shared context. If you prefer to work in isolation, this isn't the right fit. Interview Process
Intro call - Get to know each other Technical - 1-2 interviews Onsite - Coding, case study, team meet Decision - Same week as onsite We respect your time. If there's a fit, you'll know fast. Compensation & Benefits
Salary:
$200,000 - $275,000 base Equity:
Meaningful ownership in an early-stage company Healthcare:
100% of premiums covered PTO:
Unlimited, with a recommended minimum of 20 days 401(k):
4% match Equipment:
Laptop + budget for your home office Location
San Francisco - in person. (Will cover relocation costs) If you're passionate about applying frontier AI to real-world impact, join us in building healthcare's future.
Compétences linguistiques
- English
Avis aux utilisateurs
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