Senior Backend Engineer, Applied AI - Detect

Sage is on a mission to improve care and quality of life for older adults, starting with those residing in senior living facilities. Falls are the leading cause of injury-related death among adults over 65. And yet, fall prevention and emergency response systems for older adults are archaic and ineffective. At Sage we've built a more modern way of understanding when older adults need help, including methods for residents to alert caregivers when in need of help, and corresponding software for caregivers to triage response. Our company mission is to create a product that our client counterparts love, and this role is a key part of that objective.

Sage is a small, tight team of ambitious, multi-disciplinary entrepreneurs. We are a software-enabled, mission-driven company, and are focused only on the problems that are central to achieving that mission. At Sage, we work hard and fast but also know that to build a truly important company, we need to treat our work as a marathon, and not a sprint. The journey matters.

About this Role

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.

Responsibilities

• 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

Minimum Qualifications

• 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

Preferred Qualifications

• Experience with video processing, streaming protocols (RTSP/RTMP), or FFmpeg
• Hands-on experience with prompt engineering, multi-modal foundational models, and LLM/VLM optimization techniques
• Familiarity with advanced AI patterns like RAG, few-shot learning, chain-of-thought prompting, and prompt chaining
• Experience building privacy-preserving systems or working with healthcare/sensitive data
• Knowledge of cost optimization strategies for cloud-based AI services
• Experience with Dropwizard, Spring Boot, or similar JVM frameworks
• Background in building dashboards or real-time monitoring systems
• Experience with event-driven architectures and scalable data pipelines

Benefits and Pay

Our headquarters are located in New York City's Union Square. We believe in cross team collaboration. We think good ideas can come from anyone, and we've designed our processes to encourage participation from all. While we take our