Senior Software Engineer, On-Device Health Agentic Systems

We are seeking a senior iOS Software Engineer with deep experience building applications powered by Large Language Models (LLMs). This is a hands-on development role focused on creating the next generation of intelligent on-device experiences for Apple users.

You will be responsible for building cutting-edge iOS applications that serve as the primary interface for on-device AI. A key part of your role will be to explore and define the software architecture for a scalable, high-performance system that seamlessly integrates powerful LLM agents into the Apple ecosystem, all while prioritizing user privacy and on-device performance.

This role is for an expert iOS developer passionate about building the foundational architecture for AI-driven applications.

Description

What You'll Build:

- AI-Powered iOS Applications: Architect and build innovative, high-performance on-device apps that showcase the power of intelligent LLM agents.

- Scalable On-Device Architecture: Design the client-side frameworks and architectural patterns for integrating LLM systems efficiently on iOS.

- LLM Agent Integration: Implement the software that connects user-facing applications to on-device and hybrid AI reasoning and planning engines.

- Interactive AI Prototypes: Rapidly build and iterate on application prototypes to explore new user interactions and architectural options.

Impact:

This is a unique opportunity to define the future of intelligent applications at Apple. You will be at the center of building a new class of on-device experiences, setting the architectural foundation for how millions of users will interact with AI on a daily basis.

Minimum Qualifications

5+ years of professional software development with expert-level experience building high-performance, consumer-facing mobile applications and frameworks.

Strong proficiency in a modern systems programming language such as C++, ObjectiveC/Swift, or Rust. A demonstrated ability to quickly master new languages and platforms is highly valued.

Deep understanding of mobile system fundamentals: concurrency, memory management, and power optimization.

Practical knowledge of how LLM-powered systems work, including prompt engineering, agent frameworks, or RAG architectures.

Preferred Qualifications

Experience with on-device ML frameworks like Core ML, Foundation Model, etc.

Experience in SwiftUI and modern iOS architectural patterns.

Knowledge of model quantization, caching, and other on-device optimization techniques.

Experience with multi-platform development (e.g., building for both iOS and macOS).