CTO and Member of the Board | R&D for Software Defined Mobility
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Sapienza Università di Roma
Master's degree, Electrical Engineering
N/A – Present
Elektrobit
Chief Technology Officer
February 1, 2025 – Present
Elektrobit
Vice President Product R&D
July 1, 2023 – January 1, 2025
Baker Hughes
Director of Artificial Intelligence
February 1, 2020 – June 1, 2023
Florence, Italy Metropolitan Area
Continental
Head of the Artificial Intelligence & Robotics Labs
September 1, 2016 – January 1, 2020
Continental
Head of Technology Development
July 1, 2015 – August 1, 2016
Continental
Head of the AUTOSAR Center
January 1, 2009 – June 1, 2015
Continental
Manager - Software Platforms
December 1, 2007 – January 1, 2009
SiemensVDO Automotive AG
Manager - Software Platforms
January 1, 2007 – December 1, 2007
SiemensVDO Automotive AG
Manager - Speech Processing
July 1, 1999 – December 1, 2006
Fondazione Ugo Bordoni
Research Scientist
June 1, 1996 – June 1, 1999
Cultural Fit Analysis
The candidate's extensive experience is primarily in senior leadership and R&D roles, with a strong focus on innovation and strategic direction. While this demonstrates a high level of technical and managerial capability, the target role of 'Quality Assurance Engineer' is a significant shift from their career path. The lack of specific QA experience or projects might indicate a mismatch with the day-to-day responsibilities and cultural expectations of a dedicated QA engineering role. The candidate's background suggests a preference for high-level strategic and development work rather than detailed quality assurance processes.
Soft Skills & Operational Fit
The candidate's career trajectory indicates strong leadership, strategic planning, and R&D management skills. Experience in diverse technical domains (AI, robotics, speech processing, AUTOSAR) suggests adaptability and a broad operational understanding. However, the provided data does not offer direct insights into typical QA soft skills like meticulousness, attention to detail in testing, or specific collaboration styles within a QA team.