Mobile Application Software Manager
פורסם לפני 7 ימים · 0 מועמדים
התפקיד במילים פשוטות
תפקיד מנהל פיתוח אפליקציות מובייל כולל הובלה וניהול של צוותי פיתוח בארץ ובחו"ל המפתחים אפליקציות iOS ו-Android. התפקיד כולל הגדרת חזון טכנולוגי, הטמעת כלי AI בתהליכי הפיתוח, פיקוח על ארכיטקטורת התוכנה ואחריות על כל מחזור החיים של האפליקציות. מדובר בעבודה רציפה מול צוותי מוצר, חומרה וענן ברעננה.
- Experience managing distributed mobile engineering teams (25–40 engineers and tech leads)
- Hands-on engineering leadership background in mobile software development
- Native iOS and Android architectural and development expertise (Swift / Kotlin)
- Adoption and integration of AI-first software development tools and AI/ML practices into SDLC
חולץ מתיאור המשרה · מתעדכן אוטומטית
למי זה מתאים
התפקיד מתאים למנהלי פיתוח מנוסים בעלי רקע בהובלת צוותים גדולים וגלובליים (25-40 מהנדסים) וניסיון מוכח בפיתוח אפליקציות iOS ו-Android. הוא פחות מתאים למי שאינו מעוניין בתפקיד ניהולי בכיר המשלב הובלה אסטרטגית עם ניהול טכנולוגי שוטף.
תיאור המשרה המלא
המשרה המקורית · נשמר לעיוןCardo Systems, the global market leader in wireless communication systems for motorcycle and ski helmets, is seeking a talented and hands-on Mobile Application Software Manager to join our growing R&D department.
This is a full-time position based at our headquarters in Ra'anana, reporting directly to the VP of R&D.
As Mobile Application Software Manager, you will lead several distributed teams responsible for Cardo’s consumer and OEM mobile applications. Your mission is to transform our mobile organization into an AI-first engineering powerhouse, leveraging modern AI technologies and AI-driven software development practices to deliver exceptional, data-driven experiences for riders worldwide.
Key Responsibilities
Strategic Leadership
• Define and execute a unified mobile vision across B2C and B2B (OEM) products, aligning with Product Management, UX, Hardware, Cloud, and Data teams.
Team Management
• Lead, mentor, and grow teams of 25–40 engineers and tech leads located in Israel and offshore development centers.
• Foster a high-performance, collaborative, and inclusive engineering culture.
AI-First Transformation
• Drive the adoption of AI-first development methodologies across the mobile organization.
• Partner with Data Science teams to embed on-device AI/ML, personalization, and predictive capabilities into Cardo’s products.
• Champion the use of AI-powered engineering tools and workflows throughout the Software Development Life Cycle (SDLC), improving productivity, code quality, testing, documentation, and release efficiency.
Architecture & Quality
• Oversee native iOS and Android codebases (Swift/Kotlin), ensuring scalable and maintainable architecture and development best practices.
• Establish and enforce architecture standards, code quality processes, and engineering excellence.
• Lead implementation of automated testing and CI/CD pipelines using tools such as Bitrise, GitHub Actions, XCTest, Espresso, and Fastlane.
Release Excellence
• Own the end-to-end mobile delivery lifecycle, including beta programs, phased rollouts, crash analytics, A/B testing, and app store submissions.
• Ensure high-quality releases and an exceptional user experience across iOS and Android platforms.
Stakeholder Collaboration
• Work closely with Product, Hardware, Cloud, QA, Customer Success, and Business stakeholders to deliver seamless helmet-to-cloud experiences.
Metrics & Analytics
• Define and track KPIs such as user retention, crash-free sessions, engagement, feature adoption, and development efficiency.
• Use data-driven insights to guide priorities, roadmap decisions, and continuous improvement initiatives.
שאלות על המשרה
- המשרה לא ציינה שכר. אנחנו מציגים שכר רק כשהמעסיק מפרסם אותו.
- מהמשרד
- Experience managing distributed mobile engineering teams (25–40 engineers and tech leads), Hands-on engineering leadership background in mobile software development, Native iOS and Android architectural and development expertise (Swift / Kotlin), Adoption and integration of AI-first software development tools and AI/ML practices into SDLC