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Blossom Health

Applied AI Software Engineer (All Levels)

New York City$150k–$220kfulltimemidAdded today

About this role

Blossom Health, a Series A mental health tech startup, seeks an Applied AI Software Engineer to design and build scalable systems that leverage LLMs to expand access to psychiatric care. You'll own meaningful projects end-to-end in a high-trust environment, directly impacting thousands of patients and clinicians.

What you'll do

  • Design and build scalable, reliable systems for core product workflows
  • Integrate cutting-edge AI and LLM technologies into clinician and patient experiences
  • Ship high-quality, production-ready code balancing speed and technical rigor
  • Proactively identify and resolve system reliability risks, owning uptime and observability
  • Conduct code reviews and mentor teammates on engineering excellence
  • Take ownership of projects from conception to deployment with minimal oversight

What they're looking for

  • TypeScript and/or Python (LLM-powered applications preferred)
  • Full-stack systems design and implementation
  • Production system reliability and observability
  • AI/LLM integration and prompt engineering
  • Code review and technical mentorship
  • Ability to learn and adopt new technologies quickly
  • Healthcare domain understanding (preferred)
  • Startup agility and ownership mentality

Benefits

  • Competitive salary and equity
  • Best-in-class health, dental, and vision insurance
  • Unlimited PTO with outcomes-focused culture
  • Team offsites and outings
  • Sunny NYC office with stocked kitchen
  • High visibility across product, engineering, and operations in a scaling startup
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Blossom Health

Blossom Health builds an AI-native mental healthcare platform designed to expand access to psychiatric care. The company is hiring software engineers and AI engineers to develop scalable systems and own meaningful projects across the full product lifecycle.

View all jobs at Blossom Health

Likely interview questions

  • Walk us through a production system you've built end-to-end—what were the key reliability and scalability decisions?
  • Describe your experience with LLM-powered applications. What challenges did you encounter integrating AI into user-facing features?
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