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This Position reports to:
CTO Manager, RARO

We are seeking a Division Lead, Autonomous Systems Architecture, a role that sits at the cutting edge of the ongoing transformation of our business through software technology. This role centers around driving the transformation of the overall Robot Software architecture and infrastructure, spanning from real-time embedded to hardware independent AI edge-based software in our core Robotics product offering. In this role, you will report to Robotics CTO, in defining and executing technology and infrastructure roadmaps for next generation autonomous robotics, advanced simulation, multi-core real-time control systems and AI-enabled robot applications .

Key responsibilities:

• Define and implement Robot Software architecture strategy and roadmap in close collaboration with business stakeholders and global R&D teams.
• Work across global teams, each responsible for different domains of ABB Robotics product offering and technology platforms.
• Architecting hybrid systems that combine classical robotics control with modern AI approaches while maintaining reliability standards.
• Manage the end-to-end lifecycle of Robot Software architecture and infra-structure, spanning real-time embedded to hardware independent edge-based software for the core Robotics product offering, such as industrial, collaborative and mobile robots.

Qualifications:

• M.Sc. or preferably Ph.D. in Computer Science, Software Engineering, or equivalent.
• 10+ years industrial software development , 5+ years in R&D management , or R&D project management.
• Experience from embodied intelligence systems, with proven ability to design architectures bridging analytical and learned behaviors for industrial applications.
• Knowledge of reliability engineering, resource-limited systems , and high-availability architectures will be advantageous.
• Relevant and successful technology leadership experience in a R&D software environment with global, distributed teams.
• Ability to solve problems at scale and be able to derive technical as well as organizational implications of architectural decisions.

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