Sr. ADAS/AD Systems and Integration Engineer

Lucid Motors•Southfield, MI

About The Position

Join Lucid’s Autonomous Driving and ADAS organization to develop and integrate next-generation autonomy features into Lucid vehicles. This hands-on individual-contributor role works across vehicle systems, autonomy software, safety, and validation. The engineer owns assigned features from concept and requirements through integration and production readiness, with a primary focus on supervised point-to-point driving (L2++) and development work that also contributes to L4 automated driving. The role translates product goals into implementable specifications, investigates real-world vehicle behavior, and drives technical decisions across teams. It includes defining feature behavior and architecture, coordinating cross-functional integration, planning scenario-based verification and validation, analyzing vehicle and test data, resolving failures, and supporting evidence-based release decisions. The engineer also collaborates with functional safety and SOTIF specialists and coordinates with program teams, suppliers, and technology partners.

Requirements

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 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++.
Confidence interpreting logs, navigating software, using Vector tools (CANalyzer), 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.

Nice To Haves

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 evaluating rare events and coverage.
Experience with requirements and architecture tools such as Jama, DOORS, or SysML/MBSE, supplier interfaces, release readiness, or applicable NCAP and UNECE requirements.

Responsibilities

Own systems definition and delivery for assigned driving features, including 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 feature 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, connecting requirements to test methods 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 the feature scope, communicate risks and trade-offs, and coordinate with program teams, suppliers, and technology partners to support integration and evidence-based release decisions.