Perform Risk Assessment by quantifying security related safety risks, collaborating with cross functional teams particularly safety teams to ensure alignment with safety and security objectives while supporting risk-informed engineering decisions.

Drive the validation and verification of quantified risk models by designing and executing automated fuzzing pipelines and edge-case scenario testing within high-fidelity simulator environments.

Proactively identify opportunities to aggregate and integrate cybersecurity risk metrics into governance, safety, and risk management frameworks to drive strategic decision-making across the organization.

Interface with a multitude of engineering teams within Product Security as well as across software and hardware engineering. Build and maintain a strong understanding of the underlying engineering constraints and factor that understanding into the analysis and recommendations.

Research state of the art techniques to identify, analyze and defend against cybersecurity risks for autonomous vehicles and ride hailing service.

PhD in Cybersecurity/CS or related engineering field (software, hardware, systems)

Strong mathematical background with strong understanding of probabilistic risk modeling and frameworks

Pragmatic adoption of AI/LLM toolchains for security analysis and authoring high quality regulatory work products

Prior experience with quantitative risk assessment frameworks (eg: EPSS, Attack trees/graph quantification, Monte Carlo simulations, Bayesian networks)

Prior experience with the risk analysis of complex embedded systems and a demonstrated skill in turning the analysis into high-quality written deliverables

Familiarity with common cloud deployment architecture and frameworks