Responsibilities
- Take ownership of a live product with real users and make it faster, more reliable, and more capable
- Assess the existing architecture, close gaps, and build on a foundation that's already delivering value
- Architect the Health Intelligence Engine by evolving and deepening backend infrastructure, APIs, and data models that power personalized health insights
- Design systems that synthesize lab results, wearable data, symptoms, and medical history into actionable intelligence at scale
- Develop and extend data integration pipelines for lab providers (Quest, LabCorp), wearables (Oura, Apple Health, Whoop, Garmin), medical records, and user-entered data
- Ensure data integrity, security, and HIPAA compliance in data pipelines
- Build AI-powered features including conversational AI health check-ins, treatment recommendation engine, and predictive models
- Work with Claude and other AI tools to accelerate development
- Own security and compliance by building with HIPAA as a first-class concern
- Implement and maintain encryption, access controls, audit logging, and security best practices for handling sensitive health data
- Leverage AI-native development tools such as Claude, Claude Code, Cursor, and similar to accelerate building
- Embrace vibe coding and rapid prototyping to move quickly from concept to working product
- Mentor and guide additional engineers as the company scales
- Help establish engineering culture, practices, and standards
Requirements
- 10+ years of software engineering experience with a track record of building and shipping complex products
- Proven ability to work across the stack and own technical decisions end-to-end
- Strong backend and infrastructure expertise
- Deep experience with system architecture, APIs, databases, and building scalable, reliable systems
- Proficiency in Python, Node.js, or similar languages
- Experience with health data and integrations, including lab data, EHR systems, wearable APIs, or healthcare interoperability standards (HL7, FHIR)
- Understanding of the complexity of health data
- Data pipeline and ETL experience, including building pipelines that ingest, transform, and normalize data from multiple sources
- Cloud infrastructure proficiency with hands-on experience in AWS, GCP, or Azure
- Ability to architect and deploy secure, compliant infrastructure
- AI/ML implementation experience in products leveraging AI such as recommendation systems, NLP, conversational AI, or predictive models
- Security and compliance mindset with understanding of HIPAA requirements
- Ability to build systems that protect sensitive health data from the start
- Comfort with AI-native development workflows using tools like Claude Code, Cursor, GitHub, or similar
- Preference for experience with Python and Typescript
- Experience with cloud platforms like AWS, GCP, etc
- Understanding of technology health data privacy regulations including HIPAA and state telemedicine laws
- Startup mentality with experience thriving in early-stage environments where one wears many hats, moves fast, and takes ownership
- Passion for the mission of improving women's health outcomes through technology
Nice to Have
- Experience building consumer health or clinical products
- Familiarity with lab data standards (LOINC codes) and medical terminology
- Experience with wearable device integrations (Oura, Apple HealthKit, Whoop, Garmin)
- Background in building conversational AI or chatbot experiences
- Experience with mobile development (React Native, Flutter) or mobile-first web apps
- Previous founding engineer or technical co-founder experience
