Staff Software Engineer, GI Care Platform

Doist

San Francisco (CA)

Hybrid

USD 180,000 - 240,000

Full time

14 days+

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Benefits offered by this job

Dog-friendly workplace
Hybrid work model
Wellness program

Job summary

Hinge Health is expanding into GI care and seeks a Staff Software Engineer to shape end-to-end digital GI experiences. You’ll collaborate with Product, Design, and Marketing across SF, Montreal, and Bangalore to drive strategy and execution.

You will lead rapid experiments, build scalable systems, mentor teammates, and deliver a minimum lovable product, then iterate using member feedback to optimise the journey for GI end users.

Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or a related field is required.
  • 4+ years of practical software engineering experience, including building and shipping user-facing applications in production.
  • 2+ years of hands-on React Native experience building mobile applications at scale.

Responsibilities

  • Define the GI product line from scratch and set the strategic roadmap.
  • Lead the technical roadmap spanning AI systems, UX interfaces, business logic middletier, hardware integration, and collaboration with clinical leadership.
  • Develop prototypes and proofs-of-concept for the hardest parts of the new product line.
  • Build the GI product as a minimum lovable product (MLP) with measurable health improvements and iterate post-launch.

Skills

React Native
TypeScript/Node.js
GraphQL
AWS services
AI/ML integration
Mentoring engineers

Education

Bachelor’s degree in Computer Science or Engineering

Tools

GraphQL
AWS
React Native
Node.js/TypeScript
Go
SageMaker

Job description

Hinge Health is expanding into GI care and seeks a Staff Software Engineer to shape end-to-end digital GI experiences. You’ll collaborate with Product, Design, and Marketing across SF, Montreal, and Bangalore to drive strategy and execution.

You will lead rapid experiments, build scalable systems, mentor teammates, and deliver a minimum lovable product, then iterate using member feedback to optimise the journey for GI end users.

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