AI Fullstack Engineer (Health Intelligence)

TL;DR

AI Fullstack Engineer (Health Intelligence): Building and optimizing AI-powered health guidance systems for hirify.global Ring users with an accent on LLM integration, personalization, and robust evaluation pipelines. Focus on designing end-to-end product surfaces and backend workflows that transform longitudinal health data into actionable, multi-step user insights.

Location: Hybrid - Helsinki, Finland (Engineering team distributed across EU and US).

Company

hirify.global is a health technology company dedicated to empowering individuals to improve their sleep, activity, and readiness through its award-winning smart ring and connected app.

What you will do

• Design and build LLM-backed product features that deliver personalized health insights and proactive notifications.
• Lead the development of evaluation frameworks to ensure AI quality, safety, latency, and cost-effectiveness.
• Integrate AI components with frontend product surfaces to create coherent, multi-step user guidance programs.
• Collaborate on a multi-LLM platform, implementing routing logic and shadow-mode experimentation.
• Build robust, observable systems and frontend components using React to meet high performance and reliability standards.
• Partner cross-functionally with product, data science, and research teams to shape AI problem definitions and constraints.

Requirements

• 2+ years of hands-on experience in AI engineering, including frontend-heavy fullstack or applied ML roles.
• Strong proficiency in building production systems across the stack, including cloud-native services.
• Demonstrated ability to own systems end-to-end from problem framing to deployment and iteration.
• Track record of shipping product-facing features to real users rather than research prototypes.
• Comfort operating in a fast-changing AI/LLM domain with a focus on safety and pragmatism.
• Excellent communication skills for collaborating in cross-functional, distributed teams.

Nice to have

• Experience with LLM evaluation tooling (LLM-as-judge, red-teaming, prompt versioning).
• Familiarity with RAG, knowledge graphs, or semantic retrieval systems.
• Background in personalization, recommendation systems, or multi-objective optimization.
• Exposure to digital health, wearables, or behavior change domains.
• Experience with Python for backend services and data workflows.

Culture & Benefits

• Competitive salary and wellness benefits.
• Flexible working hours and wellness time off.
• Collaborative, smart team environment.
• Personal hirify.global ring provided.