Staff Software Engineer, Hinge Health

• 8+ years of non-internship full-time professional software engineering experience, with at least 2 years working on high-scale distributed systems or communication platforms
• 2+ years of experience in Python (backend/data integration) and TypeScript/Node.js (services)
• 2+ years of experience with cloud platforms (AWS preferred) and containerization tools
• 2+ years of experience working in distributed systems, microservices architectures, and large-scale data processing
• 2+ years of experience in mentoring and leading junior team members, collaborating effectively with cross-functional teams, and contributing to project planning and decision-making

Desirable

• As the Staff Engineer for the Proactive Communications team, you will lead the technical architecture and development of our unified communications platform. You will collaborate with a multidisciplinary team of Machine Learning Scientists and Software Engineers to build systems that leverage proprietary data and predictive models to orchestrate outreach across SMS, email, in-app notifications, and nudges
• As a Staff Engineer, you should be passionate about building high-quality software, have a deep understanding of distributed systems and ML integration, and be excited to work on complex challenges at scale
• We enjoy a continuous deployment DevOps culture and take owner-operator pride in supporting our code in production. Our stack includes Python, TypeScript/Node.js, AWS (Lambda, SQS, SNS, SageMaker), Go, gRPC, Kubernetes, Docker, and PostgreSQL. Our workflow is trunk-based CI/CD, and our security/compliance posture is at the highest standards of healthcare, including HIPAA, HITRUST, SOC 2, and CCPA
• Architect the Communications Engine: Lead the design and scaling of a unified communications platform that orchestrates member outreach across multiple channels (SMS, email, push, in-app) with high throughput and low latency
• Drive Technical Strategy: Define and guide the long-term technical roadmap for proactive outreach in partnership with product and engineering leadership, balancing immediate delivery with the flexibility to support future capabilities like Conversational AI
• Integrate Intelligent Interventions: Partner with ML scientists to architect systems that integrate proprietary models into communication workflows, ensuring outreach is triggered by predictive member behaviors and needs rather than static rules
• Ensure System Reliability & Scale: Optimize system performance to ensure the reliability and deliverability of member-facing messages, maintaining high standards for observability, error handling, and member privacy
• Elevate Engineering Practices: Establish and evolve best practices for CI/CD, automated testing, and monitoring for both software services and ML model performance in production
• Mentorship & Collaboration: Mentor senior and intermediate engineers, fostering a culture of technical excellence. Build strong cross-functional partnerships across Product, Design, Marketing, and Data Science to translate engagement goals into scalable technical solutions