Clera
Founding Full-Stack iOS Engineer
About this role
A Y Combinator-backed wearable AI startup seeks a founding iOS engineer to build and own their consumer companion app end-to-end. You'll translate real-time emotional-state AI outputs into intuitive, polished mobile experiences while working autonomously with a small founding team distributed across London and San Francisco.
What you'll do
- Own the iOS app architecture, development, deployment, and long-term maintenance
- Surface real-time AI emotional-state model outputs through clean, intuitive interfaces
- Build consumer-grade mobile experiences meeting high product and performance standards
- Make autonomous technical decisions and establish patterns for team scaling
- Integrate backend APIs for authentication, data sync, and model inference
- Collaborate asynchronously across distributed time zones
What they're looking for
- Swift and iOS development (3+ years production experience)
- Full-stack mobile architecture and end-to-end feature ownership
- Backend API integration and data modeling
- Machine learning model integration and inference visualization
- UI/UX design with strong performance optimization
- Independent problem-solving and technical decision-making
- Computer science fundamentals
- Remote and distributed team collaboration
Benefits
- Meaningful founding-team equity package (1–2%)
- Remote-first with flexibility for London or San Francisco presence
- Y Combinator backing with active seed funding round
- Autonomous ownership and direct reporting to founders
- Early-stage wearable AI impact on consumer emotional intelligence
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Clera
Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.
View all jobs at CleraLikely interview questions
- Walk us through a consumer iOS app you shipped end-to-end—what were the key technical decisions and how did you approach performance optimization?
- Describe your experience integrating machine learning model outputs or sensor data into a mobile UI. How did you surface complex signals intuitively?