Lead iOS Engineer (Swift) – AI-Driven & Mentorship

Zoolatech

Región Centro

Presencial

MXN 2.066.000 - 3.100.000

Jornada completa

14 días+

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Descripción de la vacante

Zoolatech is seeking a passionate Swift/iOS Engineer to lead architecture, development, and maintenance of our iOS apps for a top-tier retail client in the USA. You will help set technical direction, employ AI-native coding practices, and collaborate with cross-functional teams to deliver high-quality features.

The role emphasizes mentorship, scalable architecture, and integration of AI tools throughout the product lifecycle, with a focus on performance, testing, and code quality.

Formación

  • 6+ years of iOS development experience, including leading or mentoring engineers.
  • Deep expertise in Swift and Cocoa Touch with production apps.
  • Strong experience designing and integrating RESTful APIs.
  • Proven track record with TDD and Agile methodologies.
  • Experience integrating AI-native tools into the development lifecycle.

Responsabilidades

  • Lead the architecture, development, and maintenance of iOS apps for scalability and performance.
  • Set technical direction for iOS codebase and tooling.
  • Champion AI-native development practices across the lifecycle.
  • Collaborate with product, design, and engineering leadership to scope and prioritize features.
  • Mentor iOS engineers through code reviews and coaching on AI coding assistants.
  • Own code quality, testing strategy, and CI/CD for iOS.

Conocimientos

Swift
iOS Development
Architecture Leadership
AI-assisted Dev
TDD
Agile
Code Reviews

Herramientas

Xcode
Git
CI/CD

Descripción del empleo

Zoolatech is seeking a passionate Swift/iOS Engineer to lead architecture, development, and maintenance of our iOS apps for a top-tier retail client in the USA. You will help set technical direction, employ AI-native coding practices, and collaborate with cross-functional teams to deliver high-quality features.

The role emphasizes mentorship, scalable architecture, and integration of AI tools throughout the product lifecycle, with a focus on performance, testing, and code quality.

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