About The Position

We’re building up the core Swift platform, from architecture to CI, that enables hundreds of engineers (and their agents) to develop new capabilities in ChatGPT, Atlas, Sora, and other rapidly evolving apps. Our focus is helping teams move quickly while improving on performance or reliability. We’re hiring Staff+ engineers with a variety of iOS platform backgrounds, including people who may specialize in performance, build/CI, or AI developer productivity. Whether you focus on UI frameworks or automated testing, your work will show up as less friction, less complexity, fewer regressions, and better performance. If you're rethinking how to scale Swift development in the context of increasingly capable AI tools, this is the role for you. We are hiring in San Francisco, New York and Seattle.

Requirements

  • Have strong iOS engineering fundamentals (Swift, concurrency, networking, Xcode ecosystem, some UIKit/SwiftUI) and are familiar with the latest features and practices.
  • Gravitate towards platform problems: frameworks, architecture, performance, or tools that empower and accelerate others.
  • Take ownership: continually identify the biggest risks/opportunities, drive projects to completion, and update quickly.
  • Care about measurement: instrument, define metrics, run experiments, and iterate based on data.
  • Have strong communication and collaboration skills—aligning on interfaces, navigating tradeoffs, and driving cross-team execution.
  • Tend to think in systems, fight entropy, and enjoy an ambiguous challenge.

Responsibilities

  • Build and evolve foundational Swift frameworks used across multiple apps and platforms (caching, state management, observability, navigation, component systems).
  • Improve app performance (startup, responsiveness, memory, battery) through profiling, visibility, regression prevention, or architecture patterns.
  • Strengthen reliability: systemically reduce crashes, improve error handling, or drive release process improvements.
  • Embed with product engineering teams in order to understand pain points or emerging infrastructure needs.
  • Develop internal tooling and automation (Bazel, CI, testing, guardrails, Codex agent skills and systems) that increase engineering velocity.
  • Translate messy real-world constraints into clean abstractions: simple APIs, enforceable contracts, safe defaults.
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