Staff Backend Engineer, Sage
Applied AI, Detect
$190-245k
+ Stock Options
3+ days a week in office (Union Square, NY)
Modern operating system for senior care
Be an early applicant
Modern operating system for senior care
21-100 employees
Be an early applicant
$190-245k
+ Stock Options
3+ days a week in office (Union Square, NY)
21-100 employees
Company mission
Sage's mission is to improve the care and quality of life for caregivers and older adults.
Role
Who you are
- 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
- 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
What the job involves
- 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
Our take
In the event of an accident or fall, elder care facilities largely rely on outdated nurse call systems, which can mean residents wait longer than necessary to receive care or attention. Sage solves this problem by providing carers and institutions with a modern operating system.
Sage's caregiver app allows carers to identify patients in need of help, as well as providing tools for triage and the reviewing of care information. As one of the first companies to bring a data-driven approach to elder care in this way, Sage has received strong attention and raised an impressive $35 million in funding in 2024.
The age-tech market is growing steadily, and becoming more competitive, which means Sage will need to invest heavily in scaling its outreach in order to consolidate its progress. That said, it has established an early foothold which gives it a place to work from as it develops into the future.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Dec 2024
$35m
SERIES B
Oct 2023
$15m
SERIES A
Total funding: $59m
Company benefits
- Regular off-sites, outings, and team meals
- Office lunches and snack bars
- Stock options
- Fully-paid health insurance coverage
Company HQ
Midtown Manhattan, New York, NY
Leadership
Ellen Johnston
(CPO & Co-Founder)Was Co-Founder, Creative Director and CEO of Makr. Also worked as Director of Digital Experience at Staples.
Matt Lynch
(CTO & Co-Founder)Was a Senior Software Engineer at the Naval Surface Warfare Center, and was Software Engineering Group Lead at Palantir Technologies.
Raj Mehra
(CEO & Co-Founder)Co-founded Coupon Doc and was head of Corporate Development at Palantir Technologies. Also worked as Head of Strategy and Operations at Cedar.
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