Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience working with embedded operating systems.
Preferred qualifications:- Master's degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
About the jobIn this role, you will be responsible for defining this technical roadmap and building a engineering organization capable of solving the unique power, thermal, and latency challenges of wearable AI, ultimately ensuring architectural consistency across our entire XR hardware portfolio.
For decades, the computing revolution has reshaped our world driven by
breakthroughs in compute, connectivity, mobile, and now, AI. Google's XR team is at the forefront of the next major leap - the convergence of AI and XR. This is more than just new devices - it's about reimagining how we interact with the world around us. We're building a future where
lightweight XR devices like smart glasses and headsets pair with helpful AI to augment human intelligence, offering personalized, conversational, and contextually aware experiences.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) 20% bonus target bonus equity benefits
Responsibilities - Architect the foundational software platform (board support package (BSP), middleware, and core frameworks) that serves as the stable reference design for all future hardware iterations. Ensure the platform is modular, portable, and optimized for our specific wearable silicon.
- Partner deeply with Silicon and Electrical Engineering teams during the reference design phase to influence power budgets, thermal management, and sensor integration. Prevent downstream bottlenecks by "shifting left" on production constraints.
- Establish the technical standards, tooling, and integration patterns that allow product teams to build on top of your reference stack without architectural drift.
- Beyond the current product, define the roadmap for the platform's evolution.
- Balance the immediate demands of NPI timelines with the long-term need for a platform that can support successive generations of wearable AI.
