Job description

THINK DIFFERENT. BUILD THE FUTURE. 🚀 OUR MISSION Build everyday AGI. Trustworthy, consumer-grade agents that redefine human–AI collaboration for millions. Software shouldn’t wait for commands; it should partner with you, amplifying what you can do every single day. WHY AGI, INC. We’re a stealth team of elite founders and AI researchers, with backgrounds spanning Stanford, OpenAI, and DeepMind. We’re industry leaders in mobile and computer-use agents, bringing these capabilities to consumer scale. Grounded in years of agent research, our AI is designed with trustworthiness and reliability as core pillars, not afterthoughts. We are supported by tier-1 investors who funded the first generation of AI giants; now they’re backing us to build the next: everyday AGI. (Watch the demo drive.google.com) If you see possibility where others see limits, read on. Make AGI feel like it was always supposed to be on iPhone. Most "AI on iOS" today is a webview wrapper around a chat completion. That isn't the bar. The bar is: a user picks up their iPhone, the agent does the thing they actually wanted, and the experience feels like Apple shipped it themselves. You'll own the iOS surface for our agent — the app, the keyboard, the share-sheet integrations, the on-device runtime, and every place an Apple user expects an AI agent to show up but mostly hasn't. This is for the engineer who has strong opinions about ProMotion, who reads Apple Human Interface Guidelines for fun, and who can tell within thirty seconds of opening an app whether it was built by people who care. 🤩 TASKS YOU WILL OWN - The iOS app and SDK end-to-end — architecture, performance, and polish — alongside our CTO - Our on-device agent runtime on Apple silicon, and the Apple framework integrations (Core ML, MLX, App Intents, Live Activities, Shortcuts) - The boring-but-existential stuff — App Store review, entitlements, background execution, battery and thermal profiles 🤚 AREAS WHERE YOU WILL ASSIST - Research, by helping land models that run fast and small enough on Apple silicon - Product, by prototyping interaction patterns no one has shipped on iOS before - Android engineers, by pushing back when something deserves to be deeply native vs. cross-platform 📚 SKILLS YOU'LL BE EXPECTED TO TEACH - How to ship iOS that survives Apple review and feels first-party - How to read an iOS perf trace and find the actual bug 🧑‍🎓 SKILLS YOU'LL BE EXPECTED TO LEARN - Running LLMs on Apple Neural Engine at consumer scale - What an agent looks like with full system context vs. inside the Apple sandbox - Reliable agentic systems from the people who published the canonical papers on it 🏆 TIMELINE OF SUCCESS After 30 days — You've shipped a meaningful improvement to our iOS app — perf, polish, or a new capability — that a user would notice. You've named three things below bar and started fixing one. After 60 days — You own the iOS roadmap with the CTO. You've shipped a capability that uses an iOS-specific surface (App Intents, Live Activity, Shortcuts, or Apple Intelligence) in a way that makes the agent feel native. Other engineers ask you before they touch the iOS code. After 90 days — Our iOS experience is something you'd happily demo to an Apple engineer. You've shaped a launch and have a strong, opinionated plan for what an AGI iOS app looks like in twelve months that the team has bought into. 💰 COMPENSATION Competitive cash and meaningful equity. Top-tier relocation and immigration support. SF, in person. HOW TO APPLY Send a link to an iOS app you've built or shipped, with one paragraph on a decision you'd defend to an Apple engineer. Plus your resume, GitHub, or LinkedIn. Every exceptional candidate hears back within 48 hours.

Requirements

Must-haves

The iOS app and SDK end-to-end — architecture, performance, and polish — alongside our CTO
Our on-device agent runtime on Apple silicon, and the Apple framework integrations (Core ML, MLX, App Intents, Live Activities, Shortcuts)
The boring-but-existential stuff — App Store review, entitlements, background execution, battery and thermal profiles
Research, by helping land models that run fast and small enough on Apple silicon
Product, by prototyping interaction patterns no one has shipped on iOS before
Android engineers, by pushing back when something deserves to be deeply native vs. cross-platform
How to ship iOS that survives Apple review and feels first-party
How to read an iOS perf trace and find the actual bug
Running LLMs on Apple Neural Engine at consumer scale
What an agent looks like with full system context vs. inside the Apple sandbox
Reliable agentic systems from the people who published the canonical papers on it
After 30 days — You've shipped a meaningful improvement to our iOS app — perf, polish, or a new capability — that a user would notice. You've named three things below bar and started fixing one.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiml

Platform: ashby
Effort: quick