Full Stack Developer (USA, Remote)

Full-Stack Feature Development: Build and maintain responsive, high-fidelity web applications using React and TypeScript, backed by core services written in Spring Boot.

Backend & Distributed Systems: Architect and develop backend services that process sensitive healthcare data, leveraging message queues and streaming platforms (SQS, Kafka, Kinesis) for high-volume asynchronous workloads.

Complex Data Implementation: Design and implement the technical logic and schemas that power the platform, translating multifaceted domain requirements into structured, scalable configurations across the frontend and backend.

LLM Integration: Design and optimize LLM pipelines, including prompt engineering, usage monitoring, and quality assurance to validate structured AI outputs.

Reliability & Observability: Implement monitoring, alerting, and observability (e.g., Prometheus, Grafana), along with data reliability patterns such as redundancy, retries, and graceful failure handling.

Security & Compliance: Apply security best practices using Spring Security, implement RBAC, and help ensure HIPAA compliance for clinical data.

Platform Reliability: Proactively identify, troubleshoot, and resolve bugs and support issues across the stack to ensure a seamless experience for clinicians.

Foundational Decisions: Make technical decisions—and build the internal tooling and workflows—that will scale as we grow from ten clinics to ten thousand.

Collaboration: Work directly with founders and clinical teams to translate healthcare needs into scalable technical solutions.

End-to-End Owner: You're comfortable moving between pixel-level UI polish and backend architecture, and you own features from design through production.

Detail-Obsessed: You have an eagle eye for precision—you notice the small inconsistencies others miss, whether in UI alignment or data structures.

Systems Thinker: You reason naturally about distributed systems, failure modes, and data consistency. You design for what goes wrong, not just what goes right.

Problem Solver: You're resourceful and can find smart technical solutions when faced with complex, non-standard requirements or scaling challenges.

Ownership Mindset: You're happy to roll up your sleeves for both high-level feature work and the critical "last-mile" details that make a production system successful.

LLM Proficiency: Hands-on experience with prompt engineering to refine and validate structured AI outputs, plus usage monitoring and quality metrics.

Observability: Experience with monitoring and alerting tools such as Prometheus and Grafana.

Security & Compliance: Experience with Spring Security, RBAC, and healthcare compliance standards (HIPAA).

Reliability Patterns: Experience with redundancy, circuit breakers, retries, and graceful failure handling.

Architecture: Event-driven architectures, microservices patterns, or Domain-Driven Design (DDD).

Infrastructure as Code: Terraform, or experience with additional cloud platforms (GCP, Azure).

Performance Optimization: Proven ability to improve speed and efficiency in data-intensive applications.

Internal Tooling: A track record of building admin dashboards or automation scripts to simplify manual engineering tasks.

Healthcare technology background, audio/signal processing, real-time systems, or open source contributions.