Core Responsibilities
- Design and implement scalable backend services that ingest, transform, and persist diverse health data (wearable sensor streams, EHRs, user inputs).Build APIs and data pipelines for real-time and batch processing, ensuring data integrity, security, and compliance
- Integrate with external systems and protocols including FHIR APIs, BLE-based devices, Apple HealthKit, and Google Fit.
- Ensure backend services are designed for high availability, reliability, and low latency, especially for real-time clinical decision support
- Collaborate with security and compliance teams to ensure HIPAA-compliant handling of PHI/PII data.
- Work cross-functionally with product, clinical, and AI teams to align backend capabilities with user-facing experiences and clinical workflows
- Contribute to CI/CD pipelines, observability tooling, and data quality monitoring
- Support and mentor teammates across engineering functions, especially around secure coding and data access best practices
Requirements
- Bachelor’s or Master’s degree in Computer Science or related
- 5+ years of experience delivering products end-to-end, from ideation through planning and scoping to implementation
- Full-stack experience, including building dashboards, admin tools, or data visualizations with React/Next.js, Tailwind, etc
- Proven software architecture experience, patterns of large, high-scale applications
- Experience integrating 3rd-party health platforms and APIs, including EHRs, remote monitoring tools, or insurance data exchanges
- Background in working with data warehousing, analytics platforms, or data lakes for longitudinal health data
- Exposure to clinical workflows, remote patient monitoring, or population health management systems
- Familiarity with data governance, data provenance, and auditing frameworks for regulated environments
- Passion for writing clean, maintainable, and testable code
- Excellent programming and computer science fundamentals, and a deep love for technology
- Ability to adapt and learn new skills coupled with a resourceful, can-do attitudeOutstanding attention to detailProficient experience with Git, Github, Jira or similar project enablement tools
Technical Requirements
- Strong Python backend engineer (FastAPI, Flask, Django) with understanding of distributed systems, microservices, and asynchronous workflows (Celery)
- Solid database experience with PostgreSQL or MySQL; comfortable with Kafka or similar event-streaming systems and enforcing data contracts and idempotency
- Competent in test architecture using PyTest (fixtures, contract tests), Hypothesis (property-based testing), and Locust (performance/load testing)
- Skilled in observability and reliability engineering - instrumenting metrics, traces, and logs to measure and improve real-world system behavior
- Hands-on with Kubernetes, containerized CI/CD pipelines, and cloud environments (Azure, AWS, GCP)Familiar with OAuth2, TLS certificate management, and secure service communication
- Understands security and compliance principles (HITRUST, HIPAA, FDA 510(k)), encryption, and evidence generation for audits
- Experience with HL7 or FHIR interfaces - message parsing, composition, and secure data exchange in healthcare environments
- Systems-oriented mindset: treats testing, automation, and monitoring as first-class engineering concerns; pragmatic, collaborative, and effective across the full stackExperience with Java or other JVM-based languages preferred
- Experience with Rust
What We're Looking For
- Builder mindset with a passion for delivering robust, scalable, and secure systems in healthcare
- Comfortable working in a fast-paced, mission-driven environment where data accuracy and integrity are paramount
- Willingness to get hands dirty across the stack when needed and collaborate across disciplines
- Curious, thoughtful, and focused on long-term maintainability and resilience
- Deeply motivated by improving health outcomes through technology
Top Skills
What We Do
all.health has developed a comprehensive preventative and proactive healthcare platform that combines clinical-grade sensors, machine learning, patient histories, insurance claims data, and other information to provide real-time at-risk screening for several disease conditions; these include acute respiratory infections such as COVID-19, and chronic conditions such as hypertension and diabetes. Contextualized 24/7 data along with clinician input and interventions will then be used to guide positive behavior changes. The premise is to catch various health conditions early and help reverse or manage the negative effects.


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