Robotics Hardware Systems Architect

Robotics Hardware Systems Architect

ADI - Analog Devices

Milan, Cork or Limerick

A technical leader and electronics hardware architect for ADI’s robotics platform portfolio. This role will serve as the cross-functional hardware architect, partnering closely with leaders across applications, technology groups, software and AI, to define and evolve the architecture of our subsystem platforms (both PCB board & silicon level). Be responsible for ensuring the optimised system partitioning & scalable differentiation of complex subsystems ranging from sensing, actuation, perception, compute and safety. This role is ideal for a senior technical leader with a proven track record in robotic system design and architecture and strong systems-level thinking.

• Provide technical direction and system level architectural leadership to silicon development teams as well as across hardware teams, to deliver high-performance robotic subsystems & silicon based solutions;
• Lead and balance system trade-offs between performance, power, functional safety, complexity and cost;
• Partner with ADI AI and software teams to ensure architectural decisions are optimised from the ground up and are optimised for common simulation platforms;
• Define long-term roadmap and product direction by translating user needs, ADI core technological capabilities  & existing system performance, to determine R&D investments in line with robotic architectural evolution;
• Serve as a technical mentor and thought leader within the organization, raising the bar for engineering rigor and systems thinking.

Minimum Qualifications:

• 10+ years of experience in robotics hardware development, including at least 5 years leading system architecture;
• Deep understanding of robotic system design, particularly electronic systems;
• Proven experience in architecting and delivering complex electronic systems;
• Familiarity with functional safety concepts;
• Strong communication and collaboration skills, with experience influencing decisions across multidisciplinary teams;
• Hands-on experience with real-time control systems, and safety-rated architectures. Familiarity with AI and reinforcement learning techniques applied to robotics learning and control.