Senior Automotive Vehicle Solution Owner

Role overview Lead the direction and delivery of a vehicle body engineering solution that combines design, simulation, and data-driven methods to improve development workflows across vehicle attributes. The role draws on deep automotive experience to identify customer needs, shape product strategy, and guide work from concept to production-ready use. It combines senior customer engagement with close collaboration across engineering and machine learning teams.

Responsibilities - Own the vehicle solution end to end and define repeatable workflows for automotive engineering across body attributes. - Lead discovery with OEM and Tier 1 customers, build working relationships, validate solutions against real engineering needs, and guide scope development. - Work with CAD, CAE, and machine learning specialists to take ideas from prototype to production-ready solutions. - Equip sales, solution engineering, and marketing teams with domain insight and materials for credible discussions with automotive stakeholders. - Represent the solution in strategic technical discussions, monitor customer projects for value and alignment, and coordinate initiatives with wider product strategy.

Requirements - At least 10 years of automotive vehicle design experience, such as as a chief engineer, attribute lead, or technical lead in areas like aerodynamics, crash safety, or thermal performance. - Experience owning engineering decisions across requirements, concept development, modeling and simulation, validation, testing, and release. - Track record of building relationships with senior engineering stakeholders at OEMs. - Practical understanding of CAD, PLM, CAE simulation, physical and virtual testing, and design for manufacturing. - Familiarity with automotive body engineering workflows and tools, plus comfort with data-driven engineering. - Strong customer discovery skills and ability to move between long-term planning and hands-on cross-functional delivery.

Nice to have - Hands-on Python, AI, or machine learning experience, including applying machine learning or surrogate models to engineering design.

Benefits and work setup - Hybrid work with around 40% remote time and flexible hours. - Collaborative, multicultural team and opportunities to contribute to AI-assisted engineering.