Principal Safety Case Architect

Job description

About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career! The role We are looking for a Principal Safety Case Engineer to own the architecture, strategy and integrity of Wayve’s safety cases for our first products. This role sits independently from Engineering and Product and reports into Safety Management & Assurance, providing senior expert safety oversight while working closely with the teams responsible for designing, developing, validating and releasing the product. You will act as the architect of the safety case: defining the top-level claims, argumentation structure, evidence strategy and assurance approach that connect product intent, system behaviour, AI performance, engineering controls, validation and operational deployment into a coherent safety argument. You will provide independent challenge and advice, while enabling Engineering and Product teams to own and deliver the safety evidence required for their systems. What You’ll Be Doing Safety Case Strategy & Architecture Own the safety case strategy and architecture for Wayve’s robotaxi and OEM ADAS products. Define top-level safety claims, argumentation, evidence structures, and traceability from safety requirements through validation and deployment decisions. Develop safety arguments appropriate for AI-enabled autonomous driving, incorporating functional safety, SOTIF, AI safety, cybersecurity, validation, operational safety, and post-deployment monitoring. Evolve reusable saf…