Sage

Sage

Senior/Staff Software Engineer - Edge

New York, New York, United States · Staff+

Sponsorship not specified$175k-$230kDetected 124 days ago
JavaDistributed SystemsFull-Stack DevelopmentCode ReviewAWSCloud PlatformsLinuxMachine LearningEmbedded SystemsCommunicationPublic Speaking

About the role

  • As a Senior/Staff Backend IoT Engineer, you will be a technical leader responsible for bridging physical systems at senior living communities with the cloud computing infrastructure that powers the Sage platform.
  • Beyond individual contribution, you will mentor engineers across the team, establish engineering best practices, and serve as a key technical voice in company-wide strategic decisions.

Responsibilities

  • Lead cross-functional initiatives spanning Hardware, Cloud Infrastructure, and Client Success to deliver end-to-end solutions.
  • Mentor and grow engineers through code reviews, design reviews, and knowledge sharing.
  • Develop greenfield solutions to solve some of the most challenging problems in the senior living industry.
  • Develop software that will run on thousands of on-premise deployed systems and design the cloud systems that will allow for their orchestration.
  • Create and maintain software to create high fidelity diagnostics of edge hardware.
  • Develop full-stack services and review pull requests with the broader engineering team, raising the bar for code quality and system design.
  • Remotely troubleshoot and diagnose issues with edge deployed hardware and software, working closely with support and client success teams to systematically address root causes.
  • You will define the architectural direction for our edge computing systems and drive technical decisions that impact the entire organization.
  • We think good ideas can come from anyone, and we've designed our processes to encourage participation from all.

Requirements

  • 8+ years of software engineering experience, with significant depth in backend and/or embedded systems
  • Track record of leading complex technical projects from conception through delivery, influencing outcomes across team boundaries
  • Demonstrated ability to mentor engineers and elevate team capabilities
  • Proven experience and proficiency in Java and object oriented principles
  • Working knowledge of Linux, networking and RF communication
  • Your contributions to the edge and backend technology stacks will directly impact the ability to scale the adoption of Sage's offerings and improve the senior living industry.

Nice to have

  • Experience customizing Linux distributions for commercial deployment
  • Experience designing systems that span edge and cloud environments, including challenges like intermittent connectivity, over-the-air updates, and fleet management
  • Experience working with AWS backend technologies and distributed systems
  • Experience with some of the technologies listed here and opinions on what makes some better than others and why
  • Our headquarters are located in New York City's Union Square.
  • We believe in cross team collaboration.
  • We like to host offsites, outings, and team meals where we can connect as people, not just as colleagues.
  • Sage is an equal opportunity employer that is committed to diversity and inclusion in the workplace.

Compensation

  • Our benefits package for employees includes competitive base compensation along with stock options.

Benefits

  • Our benefits package for employees includes competitive base compensation along with stock options.
  • We also have a take as you need time off policy, in addition to 7 paid holidays and a company wide winter break during the holidays.
  • Design methods to train machine learning models that determine location of residents at senior living communities.

Company info

  • 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.
  • You will work closely with Engineering, Product, and Implementation teams to help create the next generation of software/hardware solutions that revolutionize care in senior living.
  • 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.

This listing is sourced directly from Sage's careers page and normalized into a canonical job model.