Senior Backend Engineer, Sage

• 3+ years of professional backend development experience
• Strong proficiency in Kotlin, Java, or similar JVM languages
• Experience building and maintaining distributed systems and RESTful APIs
• Demonstrated ability to debug complex production issues and optimize system performance
• Experience with cloud platforms (AWS or GCP) and containerized deployments

Desirable

• As a backend engineer for the Detect project, you'll be working on our cutting-edge AI-powered care intelligence platform that starts with fall detection but extends far beyond
• You'll tackle challenging problems at the intersection of distributed systems and applied AI - building robust video processing pipelines that handle hundreds of concurrent streams, debugging complex networking and memory issues across distributed deployments, and ensuring 99.9% uptime for life-critical systems
• At the same time, you'll shape how we leverage state-of-the-art foundational models through prompt engineering and optimization strategies to extract meaningful insights from video streams
• This role offers a unique blend: architecting scalable infrastructure, solving real-time processing challenges, optimizing system performance, while also experimenting with multi-modal AI models and crafting prompts that improve detection accuracy
• Our immediate focus is life-saving fall detection, but we're building the foundation for comprehensive care insights - creating a platform that will transform how senior care communities understand and respond to resident needs
• Design, build, and optimize real-time video processing pipelines that handle hundreds of concurrent streams, implementing fault tolerance and auto-recovery mechanisms
• Debug and resolve complex distributed systems challenges including VPN connectivity, memory optimization, concurrency issues, and stream processing failures across multiple facilities
• Improve system scalability and stability by architecting service separations, implementing proper monitoring and alerting, and ensuring 99.9% uptime
• Experiment with AI model integration, including prompt engineering for multi-modal models and implementing cost-optimization strategies like intelligent gating and caching
• Develop features and tools that surface actionable insights about resident activities, helping caregivers provide more timely and effective care
• Architect privacy-preserving video storage and replay systems, including de-identification pipelines for building long-term datasets
• Work cross-functionally with product and engineering teams to expand the platform's capabilities from acute event detection to long-term health insights