Senior Software Engineer - Backend

📋 Description

• • Architect and own the backend systems that power Qu, the clinical AI assistant trusted by thousands of clinicians worldwide. You will design domain-driven, high-availability services that orchestrate AI agents, manage real-time patient data, and enforce strict safety and compliance standards across SOC2, ISO27001, HIPAA, and GDPR.
• • Build resilient, high-throughput data pipelines that ingest, transform, and serve multi-modal clinical data (text, voice, imaging) with sub-second latency and 99.99 % uptime. Your pipelines will feed both real-time decision support and long-term analytics used by providers, payers, and pharmaceutical partners.
• • Implement event-driven architectures using FastAPI, async Python, and message queues (Kafka, Pub/Sub) to decouple services, enable horizontal scaling, and guarantee exactly-once processing of critical events such as medication orders, lab results, and AI-generated recommendations.
• • Own the orchestration layer that coordinates AI agents (see pages 15-20) across the care continuum. You will design state machines, sagas, and rollback strategies that ensure every clinical workflow is safe, auditable, and reversible—even when LLMs hallucinate or external systems fail.
• • Establish engineering excellence: enforce DDD, CQRS, SOLID, DRY, KISS, and TDD; review every PR for clarity, performance, and security; mentor junior engineers; and validate all AI-generated code before it reaches production.
• • Champion reliability and observability: define SLIs/SLOs, build distributed tracing, centralized logging, and automated alerting that surface anomalies before clinicians notice them. You will lead blameless post-mortems and turn every incident into a hardened system.
• • Collaborate daily with AI researchers, clinicians, QA, and Security to translate clinical requirements into safe, scalable software. You will participate in on-call rotations, join patient-safety reviews, and present technical designs to both engineers and medical doctors.
• • Drive continuous deployment on GCP with Kubernetes, Docker, and Terraform. You will automate everything—from infrastructure provisioning to canary releases—so new clinical features reach users within hours, not weeks, while maintaining regulatory compliance.
• • Influence product strategy by translating clinical pain points into technical roadmaps. Your systems will enable new agent capabilities (voice triage, medication reconciliation, prior-authorization) that directly reduce clinician burnout and improve patient outcomes.
• • Become the reference architect for safe, performant clinical AI. Your work will be showcased at conferences, published in case studies, and set the global standard for how AI can responsibly augment healthcare delivery.