Senior Systems Engineer, Autonomy/ADAS

About Lucid At Lucid, we are creating exceptional mobility experiences through innovation to drive the world forward. Built on Lucid’s proprietary technology and software-defined vehicle architecture, our award-winning vehicles bring our “Compromise Nothing™” approach to the global automotive market. That means refusing to choose between performance and sustainability, design and engineering, ambition and integrity. In Lucid Air and Lucid Gravity, we have designed and built vehicles that have redefined their segments, combining exceptional range, performance, design, and expansive space in a single experience. We achieve this through deep vertical integration, with design, engineering, and production happening in-house across our global offices and manufacturing facilities. Our teams come from industries around the world, united by a shared commitment to excellence. By refusing to settle, you can help redefine what’s possible and shape the future of mobility. Join Lucid’s Autonomous Driving and ADAS organization to help develop and integrate next-generation autonomy features into Lucid vehicles. Help turn advanced driving technology into safe, dependable vehicle behavior. You will own features from concept and requirements through integration and production readiness. Your primary focus will be supervised point to point driving (L2++) and development work that also contributes to L4 automated driving. This is a hands-on individual-contributor role at the intersection of vehicle systems, autonomy software, safety, and validation. You will translate product goals into implementable specifications, investigate real-world behavior, and drive technical decisions across teams. The Role: • Own the systems definition and delivery of assigned driving features: use cases, operating conditions, operational design domain (ODD), behavioral requirements, limitations, and measurable acceptance criteria. • Decompose vehicle-level objectives into functional, performance, and safety requirements. Allocate performance budgets and maintain traceability from stakeholder needs through implementation and verification evidence. • Develop functional architectures, state machines, interface specifications, and clear hardware/software ownership boundaries. Evaluate trade-offs involving sensors, compute, latency, vehicle interfaces, and algorithm capability. • Specify activation, availability, mode transitions, driver interaction, fault response, and degraded behavior. Distinguish L2 driver-supervision responsibilities from L4 system responsibilities, including fallback and minimal-risk behavior where applicable. • Partner with perception, localization, prediction, planning, controls, embedded software, vehicle integration, and HMI teams to resolve dependencies and deliver coherent end-to-end behavior. • Define scenario-based verification and validation strategies across simulation, software-/hardware-in-the-loop, proving-ground, and on-road testing. Connect each requirement to a test method and objective pass/fail criteria. • Work with data and test teams to establish feature metrics, logging needs, scenario coverage, and dataset representativeness. Use fleet and test data to identify gaps and prioritize improvements. • Investigate failures and performance limitations using vehicle logs, software behavior, and targeted experiments. Drive root-cause resolution, regression coverage, and assessment of changes across releases. • Collaborate with functional safety and SOTIF engineers on hazard analysis, foreseeable misuse, triggering conditions, safety mechanisms, and supporting evidence; incorporate relevant standards and regulatory requirements. • Lead technical reviews within your feature scope, communicate risks and trade-offs, and coordinate with program teams, suppliers, and technology partners to support integration and evidence-based release decisions. Qualifications: • Bachelor's degree in electrical, mechanical, automotive, aerospace, or computer engineering, computer science, robotics, or a related discipline, or equivalent practical experience. • 6+ years of relevant engineering experience, including hands-on systems ownership for ADAS, automated driving, or similarly complex safety-critical vehicle or robotics systems. • Experience taking a feature through requirements, architecture, integration, and verification, with clear examples of technical decisions and issues you personally resolved. • Working knowledge of the autonomy stack and its vehicle-level interactions, including sensor and compute limitations, perception/planning/control interfaces, timing, diagnostics, and degraded operation. • Ability to write testable requirements, define interfaces and acceptance criteria, manage traceability, and use scenario-based testing and quantitative analysis to assess system behavior. • Practical programming and data-analysis skills in Python or C++, and confidence interpreting logs, Vector tools (CANalyzer) navigating software, and debugging integrated systems. • Working knowledge of functional safety (ISO 26262) and safety of the intended functionality (ISO 21448/SOTIF), with the ability to collaborate effectively with safety specialists. • Strong technical communication and cross-functional problem-solving skills; comfortable owning a defined scope, documenting assumptions, and driving alignment without direct authority. Preferred: • Experience working on supervised point to point driving (L2++) OR L3/L4 autonomy • Experience with learned or end-to-end driving approaches and modular autonomy stacks, including how their limitations and trade-offs affect requirements, observability, and validation. • Hands-on vehicle integration, automotive networks such as CAN and Ethernet, and sensor/compute integration, synchronization, diagnostics, or redundancy. • Large-scale scenario mining, simulation evaluation, fleet-data analytics, SQL, or statistical methods for ev